phd in statistics italy

Department of Economics, Management and Statistics DEMS

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PhD in Economics, Statistics and Data Science

PhD in Strategic Innovation for Sustainable and Smart Ecosystems (SIS2E)
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The four-year PhD in Economics, Statistics and Data Science (ECOSTATDATA) provides the most effective response to the important challenges which nowadays doctoral programmes in the areas of economics, statistics and data analytics, both in Italy and Europe, have to cope with: i) high qualification of the faculty, in terms of teaching abilities and publication records; ii) capability of attracting high quality students; iii) interdisciplinarity; iv) internationalization; v) relations with the non-academic job market; vi) placement of students who have successfully discussed their dissertations.

ECOSTATDATA builds upon the fruitful collaboration among economists, statisticians and data scientists from the Department of Economics, Management and Statistics (DEMS) and the Department of Statistics and Quantitative Methods of the University of Milano-Bicocca (UniMiB), which has started twenty years ago within the BSc in Statistics and Economics, as well as the MSc in Statistics and Economics and is going on with the more recent MSc in Data Science.

Coordinator : Prof. Matteo Manera

Deputy Coordinator : Prof. Giorgio Vittadini

NEW!!! Call for applications 2024-2025 (XL cycle)

A.A. 2024-2025 (cycle XL)

Call for Applications

DEMS - University of Milano-Bicocca, Italy

The PhD Programme is articulated in three curricula , Economics (ECO), Statistics (STAT) and Big Data & Analytics for Business (BIDAB). The length of the PhD Programme is four years , starting in late October 2024 (the precise starting date will be announced in due course on the PhD website).

The Call of Applications 2024-2025 offers at least 10 fully-funded scholarships .

The selection procedure is regulated by the official Call for Applications (Bando di Concorso), which will be published in the Doctoral School’s and in the PhD programme websites on April 12, 2024 , with deadline on May 14, 2024.

The official Call for Applications contains detailed information on: i) the documents which each candidate has to submit; ii) structure, contents and timing (May 27, 2024 - June 21, 2024) of the entrance examination; iii) description of the projects related to the scholarships and positions offered.

The official Call for Applications will be published here .

The PhD programme (in a nutshell...)

Introduction.

ECOSTATDATA belongs to the PhD School of UniMiB, it is affiliated to DEMS, it lasts four years and it is articulated in three curricula, the original two curricula Economics (ECO) and Statistics (STAT), and, starting from cycle XXXVII (academic year 2021-2022), the “new” curriculum Big Data & Analytics for Business (BiDAB) .

The first-year teaching activities are mainly devoted to structured courses (tool courses), which are compulsory. Some of these courses are fixed and specific to each curriculum, some are in common between the three curricula, some other courses are chosen by students within each curriculum.

The second-year teaching activities take the form of less structured courses (elective courses or reading groups).

In general, the first-year courses are offered by “internal” teachers, while second-year courses are often open to the collaboration of foreign instructors (visiting scholars).

The curriculum Economics (ECO)

This curriculum is indicated to students with a strong background in quantitative economics and provides advanced training in econometrics, microeconometrics, time series analysis, microeconomics and macroeconomics.

The curriculum Statistics (STAT)

This curriculum is designed for students with a strong background in statistics, both methodological and applied , and provides advanced training in probability, stochastic processes, statistical inference, Bayesian statistics, statistical learning, statistical modelling, computational statistics and data analysis.

The “new” curriculum Big Data & Analytics for Business (BiDAB)

This curriculum starts from cycle XXXVII (academic year 2021-2022) , and provides students with rigorous training in data management and programming, with focus on: the analysis of large amounts of structured and unstructured data (natural language); the main paradigms of big data and data visualization, based on the use of innovative techniques of machine learning, text and web mining.

“Flexible” and “training” profiles

By means of appropriate sequences of courses, suggested and monitored by the Programme Committee and the supervisors, students are able to build up “flexible” profiles, which are mainly addressed to scientific research, both in universities or in non-academic institutions, at national or international level.

ECOSTATDATA facilitates the interaction between economic, statistical and data management skills by proposing innovative “training” profiles, which are mainly addressed to the non-academic job market. The “training” profiles aim at:

offering to the non-academic job market high-level skills which are not currently available;
attracting students who are interested in ECOSTATDATA as a way to gain new and advanced skills to be immediately spent into that segment of the job market which is not academically- or research-oriented;
eliciting the collaboration of high-quality national multi-national companies, which are active in human capital investment and are ready to use the instruments of the executive doctorate, the apprenticeship contracts as well as the direct financing of a PhD scholarship on specific research projects.

Length of the programme

The current length of many PhD programmes in economics, statistics and data science in Italy, including the PhD in Economics DEFAP-Bicocca and in Statistics and Mathematical Finance of UniMiB, is three years. This length is insufficient to guarantee that the PhD theses meet the quality standards achieved by the best European PhD programmes. For this reason, ECOSTATDATA lasts four years . This duration is in line with the recent choices of some of the best Italian PhD programmes in economics, statistics and data science, as well as the PhD programmes in this area offered by the most prestigious European academic institutions.

Interdisciplinarity

ECOSTATDATA fosters interdisciplinary research activities, by favouring co-tutorships between economists, statisticians and data scientists, as well as through the “flexible” and “training” profiles.

Relations with the non-academic job market

ECOSTATDATA is particularly active in collaborating with national, multi-national, high-quality and innovation-oriented companies. In particular, ECOSTATDATA is able to: i) offer high-level skills which are not currently available on the non-academic job market; ii) attract students who are interested in ECOSTATDATA as a way to gain new and advanced skills to be immediately spent into that segment of the job market which is not academically- or research-oriented; iii) elicit the collaboration of high-quality national multi-national companies, which are active in human capital investment and are ready to use the modern instruments of the executive doctorate, the apprenticeship contracts as well as the direct financing of PhD scholarships on specific research projects.

Internationalization

The international experience which has flourished within the PhD in Economics DEFAP-Bicocca and the PhD in Statistics and Mathematical Finance of UniMiB, together with the professional networks developed by many faculty members, guarantees that ECOSTATDATA is particularly active in collaborating with prestigious foreign universities, in terms of both students and faculty members exchange programs and joint degrees.

ECOSTATDATA is managed by two bodies:

the Programme Committee (PC), that is the executive and decision-making board composed by full professors, associate professors and researcher of UniMiB and from other renowned Italian and foreign universities and research institutions;
the Advisory Board (AB), which collaborates with the PC to organize the teaching and research activities of the programme, is headed by the programme Coordinator and is formed by a limited number of professors and researchers who are representative of the three curricula.

Teaching activities

The teaching activities proposed by ECOSTATDATA are organized during the first two years and differ for each curriculum, although some courses are common. Some economics courses at the first and the second year within the curriculum Economics can be offered jointly with the PhD programme in Economics and Finance of the Catholic University of Milano.

First- year courses

Curriculum Economics (selected courses)

Mathematics; Computational Statistics I; Econometrics; Microeconometrics; Time Series Analysis; Microeconomics; Macroeconomics; Research Methods; Finance.

Curriculum Statistics (selected courses)

Mathematical Analysis, Numerical Optimization, Probability, Stochastic Processes, Bayesian Statistics, Statistical Inference, Statistical Learning, Computational statistics II, Statistical Modelling, R for Data Science, Data Management.

Curriculum Big Data & Analytics for Business (selected courses)

Databases for Structured/Unstructured Data (SQL); Programming in Python; Data Quality and Cleaning for Big Data; Architecture for Big Data Processing; Machine Learning; Cloud & Distributed Algorithm; Data Mining; Natural Language processing and Understanding; Human-Centered AI; Social Media Analysis; Semantic Web; Deep Learning and Computer Vision for Business; Data Visualization & Visual Analysis.

Second-year courses

Second-year courses are mainly “reading groups”, that are built upon the research interests of both instructors and students, and are articulated into one/two introductory lecture/s and a series of meetings where students critically discuss the readings assigned by the instructor during the initial lecture.

The second-year courses are generally offered during the first part of the second year, in order forstudents to be full-time dedicated to their dissertations as early as possible.

Within each curriculum, a careful selection of courses, monitored by the PC and the student’s supervisor, allows each student to identify a “flexible” profile, which coherent with his/her research interests.

Generally, structured courses have written exams, while the exams associated with the reading groups are more flexible (e.g. written projects and/or oral presentations). The organization of the exams (i.e. form, number of questions, etc.) is decided by the PC and communicated to students at the beginning of each course.

Monitoring the quality of teaching

The PC runs every year a systematic evaluation of the quality of the courses offered by the PhD programme, by submitting to each student of a given course a detailed questionnaire. Data from the questionnaires are elaborated statistically, sent to each instructor, and discussed within the PC, in order to identify potential problems and solutions.

Admissions to the second year and to years after the second

Admission to the second year is based on the performance of each student in the first-year exams, including the number of “fail” and the number of “resits” each student has been given. Admissions to the third and the fourth years are based on the progresses of the research work. Rules on admission to the second and subsequent years, as well as all the other rules regulating the teaching and research activities of ECOSTAT are formalized by the PC and communicated to each student after enrollment.

Research activities

The Programme Committee (PC) approves the (minimum) number of papers which form a typical PhD dissertation, namely 2. These papers have to be self-contained, independent and potentially publishable on high-quality internationally refereed journals.

Supervision

In order to facilitate students in identifying a sound research project and a suitable supervisor, within the first part of the year the PC organizes a presentation of the research groups which are active among the PC and the Advisory Board (AB) members. Supervisors are asked to systematically monitor the progresses made by their supervisees and periodically report to the PC about the proceedings of their dissertations.

PhD students, especially from the second year, are strongly invited to attend the department seminars organized on a weekly basis at UniMiB. Students of both curricula are also invited to present the progress of their research work in specific seminars, which are part of the student’s evaluation process and, if possible, are jointly organized in order to enhance cross-fertilization between economists, statisticians and data scientists.

Admission to third and fourth year

Admission to the third and fourth year is formalized by the PC, based on the evaluation of the student’s research work. Admission to the third year takes also into account the performance of each student in the second-year exams.

Admission to external evaluation

Fourth-year students should present, by the end of the year, the final version of their dissertation in front of the PC. If possible, each presentation will be assigned a discussant. The admission to the external reviewers is formalized by the PC, based on the overall evaluation of the PhD thesis.

Thesis discussion

Based on the reports of the external reviewers, students are admitted to the discussion in front of the Evaluation Committee either with minor or major revisions. Students who have successfully defended their dissertation are awarded by the Evaluation Committee the title of “PhD in Economics and Statistics” (students enrolled in cycles XXXIV, XXXV and XXXVI) or the title of “PhD in Economics, Statistics and Data Science” (students enrolled from cycle XXXVII). Students can request to (and obtain from) the Administrative Offices of UniMiB an official document reporting the specific curriculum they have been enrolled in.

ECOSTATDATA takes care of the optimal placement of its students. On this respect, the Programme Committee is very active in: i) providing students with systematic and detailed information on the job market, domestic and international, academic and non-academic; ii) advising and assisting students who intend to apply for academic positions abroad.

Programme committee

Research groups.

The research activities which characterize the PhD programme in Economics, Statistics and Data Science (ECOSTATDATA) are carried out by an active and lively community of junior and senior researchers.

Within DEMS, researchers are organized in clusters , among which the most relevant for ECOSTATDATA are:

- Business, economic and social statistics (coordinator: Prof. Pelagatti)

- Empirical microeconomics and microeconometrics (coordinator: Prof. Manera)

- Experimental and behavioural economics (coordinator: Prof. Stanca)

- Macroeconomics and macroeconometrics (coordinator: Prof. Morana)

- Microeconomics: theory and applications (coordinator: Prof. Gilli)

- Statistics (coordinator: Prof. Ongaro)

- Strategy, organization and innovation (coordinator: Prof. Torrisi)

Detailed information about people involved in each cluster can be found here .

The other two main groups of researchers supporting the programme are affiliated to the Department of Statistics and Quantitative Methods (DiSMeQ) of UniMiB and to the Department of Statistics (DiSTAT), Catholic University of Milano.

Detailed information about the research activities carried on by the DiSMeQ members can be found here .

Detailed information about the research activities carried on by the DiSTAT members can be found here .

Ex-alumni - XXXIV cycle

Supervisor(s): Prof. Silvia Biffignandi, University of Bergamo

Ex-alumni - XXXV cycle

Supervisor(s): Prof. Francesca Greselin, University of Milano-Bicocca; Prof. Ricardas Zitikis, University of Western Ontario, CA

Milano PhD Workshop 2024

The ECOSTATDATA PhD students are happy to announce the second edition of the Milano PhD Workshop , that will be held at the premises of the University of Milano-Bicocca, September 23-27, 2024.

The event is jointly organized with the PhD students in economics of the major universities in the Milanese area.

The program of the event is under construction and will be available shortly.

For details you can contact the local organizers:

PhD students' seminar series 2023-2024

We are very happy to announce this new initiative: the ECOSTATDATA PhD Seminar Series!

This initiative aims to create a friendly environment where all PhD students at DEMS have the opportunity to present their own research or research proposal to obtain constructive feedback from peers and senior researchers.

Regular reminders before each presentation will be sent, and we really hope you will join this initiative. Your presence and support will be key to make this a success!

The Organizers

@Angelica Bertucci

@Ludovica De Carolis

@Matteo Ferraro

@Gregorio Ghetti

@Lorena Popescu

March 28, 2024 - Aula Seminari (U7 - 2104) 12:00

Speaker: Andrea Sorrentino

April 18, 2024 - Aula Seminari (U7 - 2104) 12:00

Speaker: Francesco Ferlaino

Field: Macroeconomics

May 09, 2024 - Aula Seminari (U7 - 2104) 17:00

Speaker: Luca Danese

Field: Bayesian Nonparametrics

May 16, 2024 - Aula Seminari (U7 - 2104) 12:00

Speaker: Angelica Bertucci

May 23, 2024 - Aula Seminari (U7 - 2104) 12:00

Speaker: Matteo Ferraro

May 30, 2024 Aula Seminari (U7 - 2104) 12:00

Speaker: Lucia Tommasiello

June 6, 2024 - Aula Seminari (U7 - 2104) 12:00

Speaker: Mattia Longhi

June 13, 2024 - Aula Seminari (U7 - 2104) 17:00

Speaker: Claudia Sartirana

June 20, 2024 - Aula Seminari (U7 - 2104) 17:00

Speaker 1: Ludovica De Carolis

Speaker 2: Jiefeng Bi

Field: Bayesian Statistics

Past events (selected) 2018-2024

The PhD in Economics, Statistics and Data Science (ECOSTATDATA), the Department of Economics, Management and Statistics (DEMS) at the University of Milano-Bicocca, joint with the Italian Society of Econometrics (SIdE), the Free University of Bolzano, the Fondazione Eni Enrico Mattei (FEEM), the International Association of Applied Econometrics (IAAE) and the Rimini Center for Economic Analysis (RCEA), have organized the 4th Italian Workshop on Econometrics and Empirical Economics (IWEEE 2024) - Climate and Energy Econometrics , at the Free University of Bolzano, during the period January 25-26, 2024.

The PhD in Economics, Statistics and Data Science (ECOSTATDATA), the Center for European Studies (CefES) and the Department of Economics, Management and Statistics (DEMS) at the University of Milano-Bicocca have organized the course Bayesian Structural VAR, held by Prof. Fabio Canova , BI Norwegian Business School, during the period November 9-14, 2023.

The PhD in Economics, Statistics and Data Science (ECOSTATDATA) and the Department of Economics, Management and Statistics (DEMS) at the University of Milano-Bicocca have organized the course Statistical Learning, held by Prof. Botond Szabo , Bocconi University, during the period October 5-27, 2021.

The PhD in Economics, Statistics and Data Science (ECOSTATDATA) and the Department of Economics, Management and Statistics (DEMS) at the University of Milano-Bicocca have organized the course Statistical Learning, held by Prof. Omiros Papaspiliopoulos , Bocconi University , during the period October 5-27, 2021. Detailed information on this course (instructor, objectives, programme, references, prerequistes) can be found here

The PhD in Economics, Statistics and Data Science (ECOSTATDATA), the Department of Economics, Management and Statistics (DEMS) at the University of Milano-Bicocca and the Fondazione Eni Enrico Mattei (FEEM), Milano, have organized the summer school on Frontiers of Energy Econometrics , at the Como Lake School of Advanced Studies, during the period September 13-17, 2021. Detailed information on the programme and the application procedure can be found on the summer school website: https://toee.lakecomoschool.org/

The PhD in Economics and Statistics (ECOSTAT) and the Department of Economics, Management and Statistics (DEMS) at the University of Milano-Bicocca have organized the course Statistical Learning, held by Prof. Rajen Shah , University of Cambridge, during the period October 5-30, 2020. Detailed information on this course (instructor, objectives, programme, references, prerequistes) can be found here.

The PhD in Economics and Statistics (ECOSTAT) and the Department of Economics, Management and Statistics (DEMS) at the University of Milano-Bicocca have organized and hosted the course Statistical Learning and Big Data, held by Prof. Sharon Rosset , Tel Aviv University, during the period October 7-18 2019. Detailed information on this course (instructor, objectives, programme, references, prerequistes) can be found here .

The PhD programme in Economics and Statistics (ECOSTAT) has sponsored the 1 st CefES International Conference on European Studies, to be held at the University of Milano-Bicocca, Building U6, on June 10th-11 th 2019. Details on this event can be found here .

The PhD programme in Economics and Statistics (ECOSTAT) has sponsored the International Conference on Econometric Models of Climate Change, held at the University of Milano-Bicocca on August 29th-30 th 2019. Details on this event can be found here .

Within the Seminar Series DEMS-ECOSTAT, Prof. Peter M Robinson (LSE), has presented the paper titled “Long-range dependent curve time series” (joint with Degui Li and Han Lin Shang). Prof. Robinson is one of the most famous econometricians worldwide and has been in the editorial boards of the most influential journals in econometrics and statistics, from Econometrica to the Journal of Econometrics, from the Journal of the American Statistical Association to the Annals of Statistics. Peter Robinson’s presentation is available here , while his paper is available here . This event has been held on February 14th 2019, 12.00am, at the Aula del Consiglio, U7, fourth floor, Piazza dell’Ateneo Nuovo 1, 20126 - Milano.

Within the celebrative events of the Twentieth Anniversary of the University of Milano-Bicocca, the Department of Economics, Management and Statistics, in collaboration with the School for Graduate Studies, has organized the International Conference on The Mathematics of Subjective Probability . This event was held on September 3rd-5th 2018, at Room U4/2, Piazza della Scienza 1, 20126 - Milano.

Within the celebrative events of its Twentieth Anniversary, the University of Milano-Bicocca, in collaboration with its School for Graduate Studies, has organized the Lectio Magistralis of Prof. Robert Engle (NYU University), winner of the 2003 Nobel Memorial Prize in Economic Sciences, on “A Financial Approach to Environmental Risk”. This event was held on June 22nd 2018, 10.00am, at the Auditorium Guido Martinotti U12, Via Vizzola 5, 20126 - Milano.

The Center for European Studies (CefES-DEMS-UNIMIB), the PhD program in Economics and Statistics (ECOSTAT-UNIMIB), and the Department of Economics, Management and Statistics (DEMS-UNIMIB) have organized the one-day international conference on Economic and Financial Implications of Climatic Change . Two plenary sessions on the economic and financial implications of climatic change have been organized on June 22 nd 2018, following Prof. Robert Engle’s talk, from 11.30am to 4.45pm, at the Auditorium Guido Martinotti U12, Via Vizzola 5, 20126 - Milano.

XXXVII cycle - Teaching activities - Year II (terms I - II) - reading groups

Reading groups (rg) offered in academic year 2022-23 (xxxvii cycle – ii year) for the curriculum in economics (eco):.

I term (October 2022 – December 2022)

- Social Network Theory (Instructor: Prof. F. Panebianco, Catholic University of Milano)

- Applications of Game Theory (Instructor: Prof. M. Gilli, University of Milano-Bicocca)

- Empirical Banking (Instructor: Prof. Elena Beccalli, Catholic University of Milano)

- Advanced Asset Pricing and Portfolio Management (Instructor: Prof. A. Tarelli, Catholic University of Milano)

- Empirical Corporate Finance (Instructor: Prof. E. Croci, Catholic University of Milano)

- Programming in Python (Instructor: Prof. L. Viarengo, Catholic University of Milano)

II term (January 2023 – April 2023)

- Spatial Models (Instructor: Prof. S. Colombo, Catholic University of Milano)

- Financial Frictions (Instructor: Prof. D. Delli Gatti, Catholic University of Milano)

- The Microeconomics of International Trade (Instructor: Prof. V. Gattai, University of Milano-Bicocca)

- Innovation and Industrial Evolution (Instructor: Prof. C. Garavaglia, University of Milano-Bicocca)

- Structural VAR Models (Instructors: Proff. V. Colombo, G. Rivolta, Catholic University of Milano)

- Applied Health Economics and Policy (Instructors: Proff. G. Turati, E. Cottini, L. Salmasi, Catholic University of Milano)

Note: the RG for the curriculum ECO are offered jointly with the PhD in Economics and Finance of the Catholic University of Milano (CUM). CUM is in charge of the timetable of each RG, whose updated version can be found here .

The following extra-RG are offered by ECOSTATDATA in the II term:

- Expected Utility and Decision Theory (Instructor: Prof. G. Cassese, University of Milano-Bicocca)

- Estimated DSGE Models (Instructor: Prof. Alice Albonico, University of Milano-Bicocca)

- Authority and Delegation (Instructor: Prof. Irene Valsecchi, University of Milano-Bicocca)

Note: the timetable of the extra-RG is available here .

Reading Groups (RG) offered in academic year 2022-23 (XXXVII cycle – II year) for the curriculum in Statistics (STAT):

I term (October 2022 – December 2022)

- The Dependent Dirichlet Process and Related Models (Instructors: Proff. F. Camerlenghi, B. Nipoti, University of Milano-Bicocca)

- Some Issues in Statistical Modelling (Instructor: Prof. R. Borgoni, University of Milano-Bicocca)

- Empirical Bayes in Bayesian Inference (instructor: Prof. S. Rizzelli, Catholic University of Milano)

- Automated Machine Learning & Neural Architectural Search (Instructor: Prof. A. Candelieri, University of Milano-Bicocca)

- Deep Learning (Instructor: Prof. M. Borrotti, University of Milano-Bicocca)

Note: the timetable of the RG for the curriculum STAT is available here .

Reading Groups (RG) offered in academic year 2022-23 (XXXVII cycle – II year) for the curriculum Big Data & Analytics for Business (BIDAB):

II term (January 2023 – April 2023)

- Databases for Structured and Unstructured Data – SQL (POSTPONED) (Instructor: Prof. F. Mercorio, University of Milano-Bicocca)

- Human-centered AI (Instructor: Prof. F.M. Zanzotto, University of Roma-Tor Vergata)

Note: the timetable of the RG for the curriculum BIDAB is available here .

XXXVIII cycle - Teaching activities - Year I (terms I - II - III - IV) - courses

The I term teaching activities start on 24 October 2022 and end on 23 December 2022. The I term exam session starts on 9 January 2023 and ends on 13 January 2023.

Note: the timetable of the I term courses is available here

The courses/modules offered during the I term for the curriculum Economics (ECO) are:

- Computational Statistics I (Instructor: Prof. G. Bertarelli, University of Pisa)

- Mathematics – Linear algebra (Instructor: Prof. N. Pecora, Catholic University of Milano)

- Mathematics I (Instructor: Prof. D. Visetti, University of Milano-Bicocca);

- Mathematics II (Instructor: Prof. F. Cavalli, University of Milano-Bicocca);

- Mathematics III (Instructor: Prof. M. Longo, Catholic University of Milano)

The courses/modules offered during term I for the curriculum Statistics (STAT) are:

- Mathematical Analysis (Instructors: Prof. C. Zanco, University of Milano; Proff. C.A. De Bernardi, E. Miglierina, Catholic University of Milano)

- Numerical Optimization (Instructor: Prof. L. Mascotto, University of Milano-Bicocca)

The courses/modules offered during term I for the curriculum Big Data & Analytics for Business (BiDAB) are:

- Programming in Python (Instructor: Prof. M. Cesarini, University of Milano-Bicocca)

- Architecture for Big Data Processing (Instructor: Prof. V. Moscato, University of Napoli)

- Architecture for Big Data Processing Lab (Instructor: Prof. G. Sperlì, University of Napoli)

The II term teaching activities start on 16 January 2023 and end on 5 April 2023. The II term exam session starts on 17 April 2023 and ends on 21 April 2023.

The courses/modules offered during the II term for the curriculum Economics (ECO) are:

- Econometrics I (Instructor: Prof. M. Manera, University of Milano-Bicocca)

- Econometrics I – Tutorials (Instructor: Dr. C. Cattaneo, European Institute on Economics and the Environment)

- Econometrics II (Instructor: Prof. M.L. Mancusi, Catholic University of Milano)

- Econometrics II – Tutorials (Instructor: Dr. E. Villar, Catholic University of Milano)

- Econometrics III (Instructor: Prof. A. Ugolini, University of Milano-Bicocca)

- Econometrics III - Tutorials (Instructor: Dr. D. Valenti, Fondazione Eni Enrico Mattei)

- Microeconomics I (Instructor: Prof. M. Mantovani, University of Milano-Bicocca)

- Microeconomics I – Tutorials (Instructor: Dr. F. Campo, University of Milano-Bicocca)

- Microeconomics II (Instructtor: Prof. M. Gilli, University of Milano-Bicocca)

- Microeconomics II – Tutorials (Instructor: Prof. M. Gilli, University of Milano-Bicocca)

- Microeconomics III (Instructor: Prof. L. Colombo, Catholic University of Milano)

- Microeconomics III – Tutorials (Instructor: Dr. D. Bosco, University of Milano-Bicocca)

- Microeconomics IV (Instructor: Prof. P. Bertoletti, University of Milano-Bicocca)

- Microeconomics IV – Tutorials (Instructor: Dr. G. Crea, University of Pavia)

Note: the timetable of the II term courses for the curriculum ECO is available here .

The courses/modules offered during the II term for the curriculum Statistics (STAT) are:

- Probability I & II (Instructor: Prof. F. Camerlenghi, University of Milano-Bicocca)

- Stochastic Processes (Instructor: Prof. B. Buonaguidi, Catholic University of Milano)

- R for Data Science (Instructor: Prof. A. Gilardi, University of Milano-Bicocca)

- Statistical Inference I (Instructor: Prof. A. Caponera, University of Milano-Bicocca)

Note: the timetable of the II term courses for the curriculum STAT is available here .

The courses/modules offered during the II term for the curriculum Big Data & Analytics for Business (BIDAB) are:

- Probability (Instructor: Prof. A. Di Brisco, University of Piemonte Orientale)

- Statistical Inference I (Instructor: Prof. R. Ascari, University of Milano-Bicocca)

Note: the timetable of the II term courses for the curriculum BIDAB is available here .

The III term teaching activities start on 26 April 2023 and end on 7 July 2023. The III term exam session starts on 17 July 2023 and ends on 21 July 2023.

The courses/modules offered during the III term for the curriculum Economics (ECO) are:

- Macroeconomics I (Instructor: Prof. G. Femminis, Catholic University of Milano)

- Macroeconomics II (Instructor: Prof. A. Albonico, University of Milano-Bicocca)

- Macroeconomics III (Instructor: Prof. R. Masolo, Catholic University of Milano)

- Macroeconomics IV (Instructor: Dr. B. Barbaro, University of Milano-Bicocca)

- Computational Statistics II (Instructor: Prof. A. Pini, Catholic University of Milano)

- Research Methods (Instructors: Prof. T. Colussi, Catholic University of Milano; Prof. K. Aktas, University of Milano-Bicocca)

- Finance I – Empirical Corporate Finance (Instructor: Prof. A. Signori, Catholic University of Milano)

- Finance II – Asset Pricing Theory (Instructor: Prof. A. Sbuelz, Catholic University of Milano)

- Finance III – Banking (Instructors: Proff. M. Migliavacca, F. Pampurini, Catholic University of Milano)

Note: the timetable of the III term courses for the curriculum ECO is available here .

The courses/modules offered during the III term for the curriculum Statistics (STAT) are:

- Statistical Inference II (Instructor: Prof. A. Solari, University of Milano-Bicocca)

- Bayesian Statistics (Instructors: Prof. R. Argiento, University of Bergamo; Proff. B. Nipoti, T. Rigon, University of Milano-Bicocca)

- Data Management (CANCELLED)

Note: the timetable of the III term courses for the curriculum STAT is available here .

The courses/modules offered during the III term for the curriculum Big Data & Analytics for Business (BIDAB) are:

- Technology and Innovation Management (Instructors: Proff. S. Torrisi, L. D'Agostino, F. Di Pietro, M. Guerzoni, University of Milano-Bicocca)

- Machine Learning (Instructor: Prof. L. Malandri, University of Milano-Bicocca)

- Natural Language Understanding (CANCELLED)

- Social Media Analytics (Instructor: Prof. R. Boselli, University of Milano-Bicocca)

Note: the timetable of the III term courses for the curriculum BIDAB is available here .

The IV term teaching activities start on 4 September 2023 and end on 20 October 2023. The IV term exam session starts on 23 October 2023 and ends on 27 October 2023.

Note: the timetable of the IV term courses is under construction and is currently shared with all the ECOSTATDATA students, who can monitor online any updates/modifications.

The courses/modules offered during the IV term for the curriculum Statistics (STAT) are:

- Statistical Learning (POSTPONED)

- Statistical Modelling I (Instructor: Prof. F. Castelletti, Catholic University of Milano)

- Statistical Modelling II (Instructor: Prof. F. Greselin, University of Milano-Bicocca)

- Statistical Modelling III (Instructor: Dr. S. Verzillo, European Commission - Joint Research Center)

- Statistical Modelling IV (Instructors: Prof. F. Pennoni, University of Milano-Bicocca; Prof. F. Bartolucci, University of Perugia)

The courses/modules offered during the IV term for the curriculum Big Data & Analytics for Business (BIDAB) are:

- Statistical Inference II (Instructor: Prof. R. Ascari, University of Milano-Bicocca)

- Explainable AI for Business Value (Instructor: Prof. F. Mercorio, University of Milano-Bicocca)

- Deep Learning and Computer Vision for Business (Instructor: Prof. E. Frontoni, Polytechnic University of Marche, TBC)

XXXVIII cycle - Teaching activities - Year II (terms I - II) - reading groups

Reading groups (rgs) offered in academic year 2023-24 (xxxviii cycle – ii year) for the curriculum economics (eco):.

I term (October 2023 – December 2023) and II term (January 2024 – April 2024)

Note: the RGs for the curriculum ECO are offered jointly with the PhD in Economics and Finance of the Catholic University of Milano. Detailed information on each RG and its timetable can be found here .

Reading Groups (RGs) offered in academic year 2023-24 (XXXVIII cycle – II year) for the curriculum Statistics (STAT):

I term (November 2023 – December 2023) and II term (January 2024 – April 2024)

Note: the timetable of the RGs for the curriculum STAT is shared online (via Google Calendar) with students officially enrolled in the PhD program.

- RG Approximate Bayesian Computational Methods (Instructor: Dr. A. Fasano, Catholic University of Milano)

- RG Automated Machine Learning & Neural Architectural Search (Instructor: Prof. A. Candelieri, University of Milano-Bicocca)

- RG Spatio-temporal Data (Instructors: Prof. R. Borgoni, Dr. P. Maranzano, University of Milano-Bicocca)

- RG Some Issues on Statistical Modelling (Instructor: Prof. R. Borgoni, University of Milano-Bicocca)

- RG Deep Learning (Instructor: Prof. M. Borrotti, University of Milano-Bicocca)

Reading Groups (RGs) offered in academic year 2023-24 (XXXVIII cycle – II year) for the curriculum Big Data & Analytics for Business (BIDAB):

I term (November 2023 - December 2023) and II term (January 2024 – April 2024)

Note: the timetable of the RGs for the curriculum BIDAB is shared online (via Google Calendar) with students officially enrolled in the PhD program.

- RG Natural Language Processing (Instructor: Dr. A. Seveso, University of Milano-Bicocca)

- RG Generative AI (Instructor: Dr. Navid Nobani, University of Milano-Bicocca)

XXXIX cycle - Teaching activities - Year I (terms I - II) - courses

The I term teaching activities start on 23 October 2023 and end on 22 December 2023. The I term exam session starts on 8 January 2024 and ends on 12 January 2024.

Note: the timetable of the I term courses is shared online (via Google Calendar) with all students officially enrolled in the PhD program.

- Microeconomics I (Instructor: Prof. Marco Mantovani, University of Milano-Bicocca)

- Mathematical Analysis I-II-III (Instructors: Prof. J. Somaglia, Polytechnic of Milano; Proff. C.A. De Bernardi, E. Miglierina, Catholic University of Milano)

- Architecture for Big Data Processing & Lab (Instructors: Proff. V. Moscato and G. Sperlì, University of Napoli)

The II term teaching activities start on 15 January 2024 and end on 27 March 2024. The II term exam session starts on 8 April 2024 and ends on 12 April 2024.

Note: the timetable of the II term courses is shared online (via Google Calendar) with all students officially enrolled in the PhD program.

- Microeconomics II (Instructor: Prof. M. Gilli, University of Milano-Bicocca)

- Microeconomics III (Instructors: Prof. L. Colombo and Dr. M. Magnani, Catholic University of Milano)

- Microeconomics IV (Instructors: Prof. P. Bertoletti, University of Milano-Bicocca, and Dr. G. Crea, University of Pavia)

- Econometrics I (Instructors: Prof. M. Manera, University of Milano-Bicocca, and Dr. C. Cattaneo, European Institure on Economics and the Environment)

- Econometrics II (Instructors: Prof. A. Ugolini, University of Milano-Bicocca, and Dr. D. Valenti, Polytechnic of Milano)

- Econometrics III (Instructors: Prof. M.L. Mancusi and Dr. E. Villar, Catholic University of Milano)

The courses/modules offered during the II term for the curriculum Statistics (STAT) are:

- Probability I-II (Instructor: Prof. F. Camerlenghi, University of Milano-Bicocca)

- Stochastic Processes (Instructor: Prof. B. Buonaguidi, Catholic University of Milano)

- Statistical Inference I (Instructor: Dr. A. Caponera, Luiss Guido Carli University)

- R for Data Science (Instructor: Dr. A. Gilardi, Polytechnic of Milano)

The courses/modules offered during the II term for the curriculum Big Data & Analytics for Business (BiDAB) are:

- Probability (Instructor: Prof. A. Di Brisco, University of Insubria)

- Statistical Inference I (Instructor: Dr. R. Ascari, University of Milano-Bicocca)

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Statistical sciences.

The PhD Course in Statistics aims at training specialists in the fields of data management and analysis and leads to a wide range of career opportunities, both in academic and research institutions.

Find out more

The doctoral programme aims to train international specialists in the fields of data management and data analysis. The programme leads to a wide range of career opportunities, both at academic level and in other highly qualified research institutions. The study project of the doctoral course is carried out according to the following steps. Start of activities. On arrival, students are informed of the regulations and the course programme for the first few months. Each student is assigned a tutor, who is available to help and guide them in their choice of research topic for the second and third year. First-year programme. The basic first-year programme comprises a core of five compulsory courses covering advanced mathematics, probability theory, computer programming, statistical theory and modelling. In addition, a number of specialised modules are offered, covering a range of more advanced topics. A side objective of the courses during the first year is to train students in group work, seminar presentations and the preparation of scientific papers. At the end of the first year, the Academic Board assesses doctoral students for admission to the second year. Admission is conditional on achieving a satisfactory level in the first year's activities. For each of the five core modules, assessment is based on a final examination. By September of the first year, students admitted to the second year propose to the Academic Board their research programme to be developed during the second and third years. Students may join local research groups or start an independent research project. The PhD programme and the Department of Statistical Sciences can provide a suitable research environment for this. Broad areas of research include: statistical methodology and its applications; statistical and econometric methods; social statistics; demography. After approval of the project, the Academic Board assigns a supervisor to each PhD student. Research programme in the second and third year. The research activity in the second and third year is the distinctive feature of the PhD programme and is aimed at achieving independent research capabilities. During the second and third years up to 12 months may be spent at a university or other highly qualified institution abroad. Students are strongly encouraged to include a period of research abroad in their programme, taking advantage of the national and international collaborative networks of the members of the Doctoral Board. The result of the research must be presented as a thesis containing original scientific results relevant to the field of statistics and its applications.

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Phd in SCHOOL OF STATISTICAL SCIENCES

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Dottorato di ricerca

The phd course, partner departments, duration, admission, scholarships, study programme, research areas, career opportunities.

The doctoral programme in Statistical Sciences at University of Padua was introduced in 1984, and was among the first Ph.D. programmes in Italy.

Starting in the academic year 2004/2005, the Department of Statistical Sciences of the University of Padua became the administrative home of the Ph.D. in Statistics.

The new programme replaced two previous research doctoral programmes in Statistics and in Statistics Applied to the Economic and Social Sciences.

The Ph.D. Course aims to provide an advanced training to support both applied and theoretical research, encouraging independence of both study and research. For a short description of the Course activities see the notice .

Partner Departments in the Ph.D. programme comprise:

- Department of Environmental Sciences, Computer Sciences and Statistics, University Ca' Foscari of Venice

- Department of Economics and Statistical Sciences, University of Udine

The PhD programme in Statistical Sciences has an expected length of 3 years. About 8 students enter the programme every year. The School aims at selecting the best candidates applying from all over the country as well as from abroad. Admission is by competition which is open to people of all ages and citizenship who already have a Diploma di Laurea (vecchio ordinamento) or Laurea Specialistica/Magistrale (nuovo ordinamento), issued in Italy, or an academic qualification of equivalent level issued by a foreign university and recognized by the academic authorities, or by interuniversity agreement of cooperation and mobility.

Basic quantitative prerequisites are assumed.

Competitions are held annually, with details being published within the Spring of each year. Courses start the following October.

For full information, see the Admission section and the page of University of Padua competition announcement .

All positions are supported by scholarships from the University of Padua or from other institutions (awarded on the basis of qualifications and oral examination). The gross annual amount of the scholarship is 16,243.00 euros , in accordance with the amount set by the D.M. MUR n. 247 of 23/01/2022. For periods of study abroad (up to 12 months) the scholarship value is increased by 50%. Moreover, an annual research budget equal to 10% of the gross annual amount of the scholarship is available for the 2nd and 3rd year. The China Scholarship Council (CSC) , offers n. 1 scholarship to candidates from the People's Republic of China .

See the Admission section and the page of University of Padua competition announcement for updates. Please, follow carefully the instructions for application in the announcement. For any additional information, please contact [email protected] .

The first year is devoted to courses, both core courses on Functional Analysis, Probability Theory, Programming Methodologies for Data Analysis, Statistical Theory and Statistical Modelling as well as short, more specialised, courses on topics such as: Time Series, Survival Analysis, Nonparametric Statistics, Survey Methodology, etcetera. Lectures are given in English . Students can also follow some upper-division courses (Laurea Magistrale) at the Department of Statistical Sciences or other Departments at the University of Padova . Attendance to all courses is compulsory .

At the end of the first year, PhD candidates propose to the Course Collegiate their own research programme to be carried over during the second and third year. They can either join local research groups at Padova or partner departments or start an independent research. The Course Collegiate assigns a supervisor to each PhD student. Original research results should be presented in the PhD thesis, to be discussed both in front of the Course Collegiate and (subject to positive evaluation by the Collegiate) in front of a Committee composed of Italian and foreign experts on the thesis topic. Intermediate results at the end of the second year are to be presented as a department seminar. During the second and third year up to 12 months can be spent at a University or other highly qualified institution abroad. In this case the grant is 50% more, for the whole period spent abroad. The thesis can be written either in Italian or in English.

For an idea of possible research subjects, see the section Alumni and the research pages of the Department of Statistical Sciences , University of Padua and of partner departments.

Broad areas of research include:

Statistical methodology and its applications . Methodological aspects range from statistical models to inference and computational issues. Applications may concern a variety of fields such as technology, industry, finance, biology, medicine, environmental studies, etc.

Statistical methods and applications in Economics . In particular: time series analysis, forecasting, statistical methods for labour economics and evaluation of public policies.

Social Statistics . In particular, survey methodology, models for individual ad aggregated data, segmentation techniques, multilevel models.

Demography . In particular, population structure and dynamics, statistical analysis of demographic behaviours and policies.

As a general objective, the Course aims at training specialists at an international level in the fields of data management and analysis. The programme leads to a wide range of career opportunities, both at the academic level and in other highly qualified research institutions. See the section Alumni for details on the current occupation of PhDs from The Department of Statistical Sciences starting from 1987.

Students having completed one of the doctoral programmes in Statistics at Padua now have positions in a wide range of academic, public and private institutions, both in Italy and abroad.

Tab. 1 Some statistics related to the professional results of the research's doctors of the PhD School/Course of the Department of Statistical Sciences of the University in Padua

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This program page was last updated on 21 April 2022. Some details may have changed since then. Please check the DEMS - University of Milan-Bicocca website or the DEMS - University of Milan-Bicocca page for current opportunities.

PhD in Economics, Statistics and Data Science at the University of Milano-Bicocca, Italy

21 april 2022, phd programs, phd in economics, statistics and data science, regular fees: 156 - 1200 eur, international fees : 156 - 1200 eur, fully funded scholarships are available, matteo manera.

The Department of Economics, Management and Statistics (DEMS) of the University of Milano-Bicocca invites applications to its PhD Programme in Economics, Statistics and Data Science (ECOSTATDATA) for the academic year 2022-23 (XXXVIII cycle). The PhD Programme is articulated in three curricula , Economics (ECO), Statistics (STAT) and Big Data & Analytics for Business (BIDAB). The length of the PhD Programme is four years , starting in late October 2022 (the precise starting date will be announced in due course).

We offer at least ten fellowships (for a period of four years) to the highest ranked applicants. Each fellowship pays a grant of a minimum of € 16.200 (gross income) per year. The monthly allowance can be increased up to 50% for our PhD students visiting academic or scientific institutions abroad. There will also be allowances (research funds) for short-period mobility (from the first year).

Additional scholarships and positions are also available on specific research projects in collaboration with national and international companies of primary importance.

The selection procedure is regulated by the official Call for Applications (Bando di Concorso), which is expected to be published in the Doctoral School’s and in the PhD programme websites on April 21st 2022 . The official Call for Applications contains detailed information on: i) the documents which each candidate has to submit; ii) structure, contents and timing (approximately during June 2022) of the entrance examination; iii) description of the projects related to the additional scholarships and positions.

The link to the official ECOSTATDATA website can be found here , while the link to the official Call for Applications can be found here .

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4 PhD fellowships available at SISSA - Physics and Chemistry of Biological Systems

programme Is the Job related to staff position within a Research Infrastructure? No Offer Description PhD in Physics and Chemistry of Biological Systems SISSA welcomes applications for 4 PhD fellowships in

Researcher on Big Data and Artificial Intelligence

/Qualifications PhD in Computer Science or related field (with preferred specialization in Machine Learning/Deep Learning); Documented experience in Machine learning and Deep neural network model design and

PNRR Project - CN NBFC (National Biodiversity Future Center) – Id. project nr. CN_00000033 - CUP B83C22002930006

, gene-environment association and landscape genomics, knowledge of GIS computing environments and spatial statistics analysis, bioinformatics skills concerning the management and analysis of large-scale

Tenure Track position for a Mathematical Modeller of Infectious Diseases at Bruno Kessler Foundation, Centre for Health Emergencies.

in the epidemiology and modelling of infectious diseases. Its main focuses are: ● mathematical and statistical modelling of infectious diseases transmission; ● epidemiology of emerging infectious

Postdoc position in Bioinformatics - 3D chromatin architecture and ncRNAs

of data and generation of figures for grant proposals, presentations and publications in peer-reviewed journals Essential requirements · A PhD in Bioinformatics, Computational Biology, Computer

PhD position on Assessing and predicting the fate of model pharmaceutical compounds and their transformation products in soils & towards the aquatic systems

such as environmental consultancies and agencies. DESCRIPTION OF THE PhD PROJECT Veterinary pharmaceutical compounds (PhACs) and their transformation products (TPs) enter soil, then water bodies, through

Technician of the Biostatistics Unit (statistician/ statistical geneticist) - Centre for Genomics

analysis languages, ideally R or Python. PhD or equivalent qualification in a relevant subject, e.g. Statistics , statistical genetics or epidemiology; Documented experience with using common statistical

The Physics of Chromosome Folding

to staff position within a Research Infrastructure? No Offer Description Equilibrium and non-equilibrium statistical mechanics; soft-matter physics; coarse-grained models; stochastic dynamics

Researcher in large-scale multi-omics data analysis

of scientific results through conference contributions and scientific publications. Requirements: PhD within relevant field of research (Bioinformatics, Biostatistics, Computational Biology). Experience in large

Resilience factors in the development of students from low-income families

LevelMaster Degree or equivalent Research FieldPsychological sciencesEducation LevelPhD or equivalent Skills/Qualifications University degree: Master of Science in psychology, Cognitive Science. A PhD degree in

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PhD in Statistical Sciences

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Monica Chiogna

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Via Belle Arti 41 Bologna (BO)

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PhD Scholarship in Statistics and Computer Science (Cohort 2020-21), Università Bocconi, Italy

PhD Scholarship in Statistics: The Department of Decision Sciences is offering a prestigious 4-year PhD scholarship in Statistics and Computer Science under the direction of Prof. Antonio Lijoi. This program, expanding from the successful PhD in Statistics, aims to develop strong mathematical, statistical, computational, and programming skills. It emphasizes the cross-disciplinary nature essential for gaining first-class research skills, particularly in the evolving fields of Machine Learning and Data Science.

Summary Table:

Study Area: The PhD program focuses on Statistics and Computer Science , providing a cross-disciplinary approach essential for modern data scientists.

Scholarship Description:

PhD Scholarship in Statistics and Computer Science (Cohort 2020-21)

This 4-year PhD program offers a rigorous curriculum that develops strong mathematical, statistical, computational, and programming backgrounds. Students can choose between two tracks – Statistics and Computer Science – during the first year, followed by track-specific courses and elective courses in the second year. The third and fourth years are dedicated to the doctoral thesis.

Eligibility: This scholarship is tailored for extremely talented and motivated students seeking expertise as statisticians with a deep knowledge of computing or computer scientists with a strong background in probabilistic and statistical modeling.

Required Documents: Interested applicants should submit the following:

Application form
Curriculum vitae (CV)
Academic transcripts
Letters of recommendation
Research statement

How to Apply: Submit the required documents to the email address provided on the program’s official website.

Last Date for Apply: Until position filled

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Post-doctoral fellow in carbon dynamics, Lund University, Sweden

10 Degrees in Statistics in Italy for 2024

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Bachelor in Statistical Sciences: Stats&Maths

University of bologna.

Bologna, Italy

Stats&Maths bachelor’s degree in Statistical Sciences (first cycle) trains junior experts and technicians to work professionally in the statistical field.

MSc Actuarial Sciences, Risk and Data Analysis

Università cattolica del sacro cuore.

Milan, Italy

Strong knowledge of statistical methodology and its applications in the field of economics, economic-management, finance, demography, sociology, insurance and social security

Master in Statistical Sciences

The International Master's (Second Cycle Degree) in Statistical Sciences aims to train experts able to manage, analyze and interpret data in order to produce that knowledge required to support decision-making processes in private and public companies.

Master in Statistics, Economics and Business: Business Analytics

The new 2-year international Master in Business Analytics aims to prepare students from a variety of backgrounds for a career as business analysts in modern private and public organizations. The Programme is designed for students with a strong propensity for computational and statistical sciences as well as a strong interest in working with data.

Master of Science in Statistical Methods and Applications

Sapienza university of rome.

Rome, Italy

SMA - Statistical Methods and Applications - is the acronym of the two-year international Master of Science entirely taught in English and delivered by the Department of Statistical Science (DSS). DSS is the largest Department of Statistics in Italy and its faculty members enjoy an international reputation in teaching and research.

PhD Course in Mathematics, Computer Science, Statistics

University of florence.

Florence, Italy

English, Italian

The PhD program in "Mathematics, Computer Science, Statistics", based in Firenze, is managed by a Consortium among the University of Firenze, the University of Perugia and the Istituto Nazionale di Alta Matematica "F. Severi"-Rome (INdAM). This PhD program inherited the tradition of the pre-existing three separate PhD's in Mathematics, Computer Science, Statistics, and can rely upon the very many, and well established, scientific connections of the involved institutions with Universities and Research Centers in many Countries of the World. The relevant number of offered scholarships allows the achievement of a critical mass of PhD students and activities, which are fundamental for a doctorate with an interdisciplinary character.

Statistics for Sample Surveys

University of siena.

Siena, Italy

The master's degree course has the aim of adequately preparing graduates for getting jobs in both the public and private sectors; by providing capacities for the treatment of large databases, and for planning and implementing sample surveys in various fields, with a major focus on socio-economic and environmental sectors.

Diploma Supplement

Mediterranean agronomic institute of bari ciheam iamb.

Bari, Italy

Advanced Diploma

Diploma Supplement Since 2007, CIHEAM Bari has been issuing a Diploma Supplement (DS) to all students who are awarded the Master and Master of Science Diploma. What is a Diploma Supplement? The Diploma Supplement (DS) aims at improving international transparency and facilitating the academic and professional recognition of qualifications. It provides a description of nature, the level, the context, the content, and the status of the studies that were successfully completed by the person concerned. The Diploma Supplement is not a resume, a diploma, a transcript of records, and it is not an automatic system of recognition. It consists of eight sections: 1. Information identifying the holder of the qualification 2. Information identifying the qualification 3. Information on the level of qualification 4. Information on the grading scheme and results gained 5. Information on the function of the qualification 6. Additional Information 7. Certification of the supplement 8. Information on the national system of higher education What are the advantages of the Diploma Supplement? For the student A document that offers a description (and not an assessment) of the originality of a pathway as well as the resulting skills A means to promote national and international mobility An asset for professional integration.

Master in Statistical and Actuarial Sciences

University of sannio.

Benevento, Italy

The Study Course in Statistical and Actuarial Sciences has been established at the University of Benevento since 1991. It represents a unique educational offer in Campania and in southern Italy. Similar study paths are present only in the universities of Rome "La Sapienza" and Trieste. The Master's Degree Course in Statistical and Actuarial Sciences aims to train highly qualified professionals in the field of actuarial sciences and applied quantitative methodologies in the category of insurance, social security, and financial issues.

PhD in Statistical Physics

International school for advanced studies (sissa).

Trieste, Italy

Statistical Physics, together with Quantum Mechanics, is the pillar of our understanding of many physical phenomena, from the simplest to the most sophisticated. The field has recently witnessed a significant and impressive outpouring of experimental and theoretical results,

Popular degree type

Popular study format

Popular education type

Degrees in Statistics

How do researchers determine what is true based on the data they collect? This question is one of the central concerns of statistics, which uses mathematical models to draw useful conclusions about the real world.

Officially known as the Italian Republic, the country is found in southern Europe. The official language is Italian and the cultural rich capital is Rome. Many of the world's oldest universities are located in Italy, in particular the University of Bologna (founded in 1088). There are three Superior Graduate Schools with "university status", three institutes with the status of Doctoral Colleges, which function at graduate and post-graduate level.

Engineering students gain real-world knowledge for future success during Italy trip

Lucas Johnson

Apr 15, 2024, 6:35 AM

by Lucas Johnson

More than 20 Vanderbilt engineering students recently visited Italy during their spring break to not only see some iconic structures, but also learn the engineering behind the Pantheon and Venice’s sophisticated floodgates so they could apply that knowledge to future engineering projects of their own.

The trip was part of an inaugural class taught this semester in the Civil and Environmental Engineering Department and sought to give the 22 students a deeper understanding of the engineering behind some of Italy’s structures, such as the ancient Pantheon and MOSE project designed to protect the city of Venice from flooding. The MOSE project is an integrated system consisting of rows of mobile gates that uses air pressure to keep water levels in check.

As part of their class assignments, the students worked in groups to design floodgates as well as build and test concrete dome prototypes based on their studies of how the Pantheon was constructed. The class was originally scheduled for 15 students, but instructors increased the number because of interest.

“We wanted to help students understand the history and the beauty of structural engineering with the hope that they will be able to better work with architects to achieve beautiful and structurally sound buildings in their careers,” said Lori Troxel, professor of the practice of civil and environmental engineering and a class instructor.

While in Italy, the students traveled to Rome, Venice, and Milan. In Milan, they spent time with architects who had worked with the renowned architect Zaha Hadid, and met with a group of students from Polytechnic University of Milan who were taking a class on structural health monitoring. In Venice, they talked to engineers involved with the city’s unique flood gates. And in Rome, the students visited ancient sites like the Pantheon, the Coliseum, and the Roman Forum.

Winnie Huang, a junior majoring in civil engineering, marveled at the construction of the Pantheon.

“Seeing the Pantheon in person made clear why its design has allowed for it to last thousands of years,” said Huang. “Despite the cracking as a result of the hoop stresses of the dome, the Pantheon has notably stayed structurally sound due to its construction with Roman concrete, which contains self-healing properties. Although we didn’t personally have the opportunity to work with Roman concrete for our project, we took inspiration from the Pantheon in designing our own miniature concrete dome.”

For Santino Clemente, whose grandparents are Italian immigrants, the trip was his third time in Italy and one he had looked forward to because after each visit he found himself wanting to go back. Before the latest trip, he watched a documentary about the MOSE project.

“Being there in person and getting to ask all our questions to the engineers was an awesome experience,” said Clemente, a junior majoring in mechanical engineering.

After returning from Italy, the students tested floodgates they had constructed in a creek at a park near the university. In constructing the floodgates, they had a budget of $50 and could use whatever scrap materials they found.

Philmon Gashaw, also a junior mechanical engineering major, said his group used a magnet, wood, and acrylic to design their floodgate. “We put it in the creek and saw how well we could stop the water,” said Gashaw. “It worked surprisingly better than I thought.”

Many of the students applied what they learned about the MOSE project to the construction of their floodgates. For Clemente and his team, he said it was the angle for the wall of their floodgate.

“We learned that the MOSE gates are lifted up to a 42-degree angle to prevent a straight-on impact from the tide, which would result in a much higher force,” he said. “Therefore, even though the top of our gate was fully vertical, we added a ramp at the bottom that guided the water upward. This prevented the water from pushing our floodgate on first impact.”

Ghina Absi, assistant professor of the practice of civil and environmental engineering and a class instructor, said she enjoyed seeing the students’ engagement and excitement as they worked on the projects, and hopes what they learned will benefit them down the road.

“Even when they’re trying to solve a tiny problem of stopping a flow in a tiny channel next to campus, they will be able to take all the lessons they’ve learned and apply them to the big project I know they are capable of doing in the future,” said Absi.

Last year during spring break, Troxel led a group of engineering professors and students to Israel as part of a different program to learn about the country’s water recycling programs and bring those lessons back to share with Sterling Ranch, a 21st century sustainable city south of Denver, Colorado, that has doubled as a training site and test bed for Vanderbilt students and professors since 2015.

Trips to destinations like Italy and Israel also highlight experiential learning opportunities through an academic degree requirement called Immersion Vanderbilt , which provided funds to reduce student costs for the trip to Italy.

“There’s no better way for students to learn than to provide them with real-world experience,” said Cynthia Paschal, senior associate dean for undergraduate education. “Study abroad initiatives like these are examples of the ways Vanderbilt is assuring our students are prepared to compete on a global stage.”

The Italy trip was made possible by generous financial support from FINFROCK, a leader in design-build construction in Central Florida. The Department of Civil and Environmental Engineering provided a staffer to help with organization and on-site logistics, and the School of Engineering provided support to ensure that all students could participate, regardless of their financial circumstances.

Contact: Lucas Johnson, [email protected]

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Spring 2024 Graduate Research Awards from the Department of Statistics

Iowa State University has announced the recipients for the Spring 2024 Graduate Research Excellence Awards. Among these distinguished scholars stand three individuals from the Department of Statistics, whose outstanding research contributions have garnered well-deserved recognition.

Eva Biswas (Nominator: Somak Dutta)

Nomination statement: Eva Biswas has demonstrated outstanding research achievements. She has made remarkable contributions to theory and methods for time series, functional data, Markov random fields, directional statistics, and applications of statistical methods in plant science. She has two published papers, two under major revision, and is working on finishing four more.

Yonghyun Kwon (Nominator: Jae-Kwang Kim)

Nomination statement: Yonghyun has recently completed his PhD. His academic portfolio includes four papers that have been published or accepted in peer-reviewed journals, along with one paper currently under review by the Journal of the American Statistical Association (JASA).

Yunhui Qi (Nominator: Peng Liu)

Nomination statement: Yunhui Qi is a dedicated researcher in statistics and a great collaborator with biologists. She has a genuine interest in research and has made significant advancements in several challenging problems in multi-omics data analysis.

Eligible students are those enrolled at Iowa State University and nearing completion of their thesis or dissertation. Candidates embody excellence in research, academic prowess, and a passion for scholarly exploration, showcasing a profound understanding of their field. With strong analytical skills and a commitment to collaboration, they tackle complex research questions with creativity and rigor. Each recipient receives a commendation letter from the Iowa State President, a certificate of achievement, an honor cord for commencement, and an official notation on their transcript.

Join us in congratulating these exemplary scholars from the Department of Statistics for their achievements and contributions to statistical research.

Biostatistics Graduate Program

Shengxin tu wins 2024 provost pathbreaking discovery award.

Posted by duthip1 on Wednesday, April 17, 2024 in News .

PhD candidate Shengxin Tu has been named a recipient of Vanderbilt’s Provost Pathbreaking Discovery Award , which “recognizes doctoral students who exhibit exceptional academic excellence in publications, awards, patents, and other forms of national or international distinction” with $2,500 in supplemental funding. Tu is first author of a recent paper in the prestigious Statistics in Medicine journal, as well as second author of a retrospective cohort study discussed in last month’s Journal of the International AIDS Society. Tu currently serves as secretary of the Biostatistics Graduate Student Association and has completed internships at Genetech and Amazon; she is also presently a research assistant with CCASAnet , the Caribbean, Central and South America network for HIV epidemiology.

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Italy: Number of free-floating bike sharing trips 2017-2022

The number of trips on free-floating shared bikes in Italy peaked in 2022, when users made nearly 9.7 million trips. In 2021, trips on free-floating shared bikes stood at just under 4.7 million.

In free-floating bike-sharing schemes, bicycles do not need to be returned to the same location where they were picked up but can be dropped off anywhere within a usually pre-determined geographic area.

Number of free-floating bicycle sharing trips in Italy from 2017 to 2022

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Fondazione per lo Sviluppo Sostenibile

October 2023

2017 to 2022

Excludes touristic services and bike sharing services with a fleet smaller than 80 vehicles.

Statistics on " Active and micromobility in the United Kingdom "

Selected European countries: walking modal share as a primary mode of transport 2022
Cycling as primary form of transport for short journeys in Europe 2022
Primary form of transport for short journeys in Great Britain 2022
Selected cities in the UK ranked for access to climate-friendly mobility, 2022
Number of bicycle sales in the European Union 2018-2022
England: adults who walked for travel and leisure in 2021, by frequency
Northern Ireland: share of residents likely to walk for journeys up to 2 miles by age
Scotland: walking frequency in the previous 7 days, 2021
Wales: frequency of walking for the purpose of travel, 2022/2023
England: cycling frequency of people above five years old 2020-2021
Northern Ireland: cycling frequency in the last 12 months
Frequency of cycling for pleasure or transport in Scotland 2021
Proportion of people who cycle for transport in Wales in 1-2022, by frequency
Bicycle sales in Great Britain 2000-2022
Electric bike sales in Europe 2022, by country
Non-motorized bicycles: UK manufacturer sales volume 2012-2022
Non-motorized bicycles: UK manufacturer sales 2012-2022
Bike popularity by average monthly search volume in the UK 2021
Shared mobility vehicle fleet in British cities 2022
Selected cities in the UK ranked by access to shared bikes and e-scooters 2022
Use of bike-share in the UK at least once a week, by purpose 2022
Projected revenue and ARPU forecast of bike-share market in the UK 2022-2027
User forecast of e-scooter sharing market in the UK 2022-2027
Selected cities in the U.K. ranked by space for walking and cycling 2022
UK: attitude towards improvement of cycling infrastructure, 2022
UK: percentage of residents who would be motivated to cycle with better facilities
Great Britain: pedal cycle mileage by road class 2021-2022
Proportion of residents in the UK who think walking or wheeling in their area is safe
Selected cities in the UK ranked for cyclist and pedestrian safety 2022
GBR: Pedestrian and pedal cyclist casualties per billion traveled miles 2019-2021
Reported e-scooter casualties by age and sex in Great Britain 2022
England: number of pedestrian and pedal cyclist casualties 2017-2021
Northern Ireland: number of pedestrian and pedal cyclist casualties 2018-2023
Scotland: pedestrian and pedal cyclist casualties by level of injury, 2022
Pedestrian and pedal cyclist casualties in Wales 2020-2022

Other statistics that may interest you Active and micromobility in the United Kingdom

Premium Statistic Selected European countries: walking modal share as a primary mode of transport 2022
Premium Statistic Cycling as primary form of transport for short journeys in Europe 2022
Premium Statistic Primary form of transport for short journeys in Great Britain 2022
Premium Statistic Selected cities in the UK ranked for access to climate-friendly mobility, 2022
Premium Statistic Number of bicycle sales in the European Union 2018-2022

Active and micro-mobility use

Premium Statistic England: adults who walked for travel and leisure in 2021, by frequency
Premium Statistic Northern Ireland: share of residents likely to walk for journeys up to 2 miles by age
Premium Statistic Scotland: walking frequency in the previous 7 days, 2021
Premium Statistic Wales: frequency of walking for the purpose of travel, 2022/2023
Premium Statistic England: cycling frequency of people above five years old 2020-2021
Premium Statistic Northern Ireland: cycling frequency in the last 12 months
Premium Statistic Frequency of cycling for pleasure or transport in Scotland 2021
Premium Statistic Proportion of people who cycle for transport in Wales in 1-2022, by frequency

Bike market

Premium Statistic Bicycle sales in Great Britain 2000-2022
Premium Statistic Electric bike sales in Europe 2022, by country
Premium Statistic Average e-bike price in selected European countries 2022
Basic Statistic Non-motorized bicycles: UK manufacturer sales volume 2012-2022
Basic Statistic Non-motorized bicycles: UK manufacturer sales 2012-2022
Premium Statistic Bike popularity by average monthly search volume in the UK 2021

Shared micro-mobility

Premium Statistic European shared mobility ridership growth 2022 to 2023
Premium Statistic Shared mobility vehicle fleet in British cities 2022
Premium Statistic Selected cities in the UK ranked by access to shared bikes and e-scooters 2022
Premium Statistic Use of bike-share in the UK at least once a week, by purpose 2022
Premium Statistic User forecast of bike-sharing market in the UK 2022-2027
Premium Statistic Projected revenue and ARPU forecast of bike-share market in the UK 2022-2027
Premium Statistic Key players in the bike sharing market of the UK 2022
Premium Statistic User forecast of e-scooter sharing market in the UK 2022-2027

Infrastructure

Premium Statistic Selected cities in the U.K. ranked by space for walking and cycling 2022
Premium Statistic UK: attitude towards improvement of cycling infrastructure, 2022
Premium Statistic UK: percentage of residents who would be motivated to cycle with better facilities
Premium Statistic Great Britain: pedal cycle mileage by road class 2021-2022
Premium Statistic Proportion of residents in the UK who think walking or wheeling in their area is safe
Premium Statistic Selected cities in the UK ranked for cyclist and pedestrian safety 2022
Premium Statistic GBR: Pedestrian and pedal cyclist casualties per billion traveled miles 2019-2021
Premium Statistic Reported e-scooter casualties by age and sex in Great Britain 2022
Premium Statistic England: number of pedestrian and pedal cyclist casualties 2017-2021
Premium Statistic Northern Ireland: number of pedestrian and pedal cyclist casualties 2018-2023
Premium Statistic Scotland: pedestrian and pedal cyclist casualties by level of injury, 2022
Premium Statistic Pedestrian and pedal cyclist casualties in Wales 2020-2022

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The four-year PhD in Economics, Statistics and Data Science (ECOSTATDATA) provides the most effective response to the important challenges which nowadays doctoral programmes in the areas of economics, statistics and data analytics, both in Italy and Europe, have to cope with: i) high qualification of the faculty, in terms of teaching abilities and publication records; ii) capability of ...
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Statistical Sciences. Thematic area Hard Sciences. Duration 3 years. Language English. PhD Programme Coordinator Nicola Sartori. Web site. The PhD Course in Statistics aims at training specialists in the fields of data management and analysis and leads to a wide range of career opportunities, both in academic and research institutions.
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The Ph.D. Programme "School of Statistical Sciences" ("Scuola di Scienze Statistiche") consists of three curriculum: (a) Demography; (b) Actuarial Sciences; (c) Methodological Statistics. Their description is provided below. The doctoral program in Demography aims to train researchers and highly professional figures for all the roles where ...
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5 Statistics PhDs in Italy. This page shows a selection of the available PhDs in Italy. If you're interested in studying a Statistics degree in Italy you can view all 5 PhDs. You can also read more about Statistics degrees in general, or about studying in Italy. Many universities and colleges in Italy offer English-taught PhD's degrees.
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Available PhD positions Leggi dettagli About 5 PhD studentships for A.Y. 2024/25 will be available at University of Bologna for candidates interested in any area of Statistical Sciences (start of activities: November 1st, 2024).
PhD in Statistics and Computer Science
PhD program Director Prof. Antonio Lijoi PhD Administrative Assistant Angela Baldassarre. The 4-year PhD in Statistics and Computer Science is a high profile and rigorous doctoral program, within the Department of Decision Sciences, that develops strong mathematical, statistical, computational and programming backgrounds. It arises as an expansion of the PhD in Statistics, which has been ...
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5 NRRP PhD studentships for A.Y. 2023/24 are available at the University of Bologna for candidates interested in the area of Statistical Sciences (start of activities: November 1st, 2023). The grants are linked to the development of special PhD projects (see Admission). Go to page. Insert here a short description.
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All studies; Computer Sciences; Europe; Italy; Università Commerciale Luigi Bocconi; Statistics and Computer Science ; About. The 4-year PhD in Statistics and Computer Science at Università Commerciale Luigi Bocconi is a high profile and rigorous doctoral program, within the Department of Decision Sciences, that develops strong mathematical, statistical, computational and programming ...
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PhD Scholarship in Statistics and Computer Science, Italy
PhD Scholarship in Statistics and Computer Science (Cohort 2020-21), Università Bocconi, Italy. November 17, 2023. PhD Scholarship in Statistics: The Department of Decision Sciences is offering a prestigious 4-year PhD scholarship in Statistics and Computer Science under the direction of Prof. Antonio Lijoi.
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14 Master's degrees in Statistics in Italy
Check match. 2,800 EUR / year. 2 years. The Master's Degree in Stochastics and Data Science at University of Turin aims preparing students with a solid and modern education in probabilistic and statistical methods. M.Sc. / Full-time, Part-time / On Campus. University of Turin Turin, Italy. Ranked top 2%. Add to compare.
Engineering students gain real-world knowledge for future success
Vanderbilt University is committed to the principle of equal opportunity. Vanderbilt University does not discriminate against individuals on the basis of their race, sex, sexual orientation, gender identity, religion, color, national or ethnic origin, age, disability, military service, or genetic information in its administration of educational policies, programs, or activities; admissions ...
PhD in Statistics
The PhD in Statistics was established within the Bocconi PhD School in 2001 by Pietro Muliere, who was also the first Director of the program and was later succeeded by Sonia Petrone. The four-year PhD program in Statistics gives a solid theoretical grounding for high level research in universities and international institutions .
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PhD candidate Shengxin Tu has been named a recipient of Vanderbilt's Provost Pathbreaking Discovery Award, which "recognizes doctoral students who exhibit exceptional academic excellence in publications, awards, patents, and other forms of national or international distinction" with $2,500 in supplemental funding. Tu is first author of a recent paper in the prestigious ...
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