phd data science austria

17 Best universities for Data Science in Austria

Updated: February 29, 2024

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Below is a list of best universities in Austria ranked based on their research performance in Data Science. A graph of 226K citations received by 7.94K academic papers made by 17 universities in Austria was used to calculate publications' ratings, which then were adjusted for release dates and added to final scores.

We don't distinguish between undergraduate and graduate programs nor do we adjust for current majors offered. You can find information about granted degrees on a university page but always double-check with the university website.

1. Vienna University of Technology

For Data Science

2. University of Vienna

3. Johannes Kepler University Linz

4. Graz University of Technology

5. University of Innsbruck

6. Medical University of Vienna

7. Vienna University of Economics and Business

8. University of Graz

9. University of Salzburg

10. Medical University of Graz

11. Medical University of Innsbruck

12. University of Natural Resources and Applied Life Sciences, Vienna

13. Danube University Krems

14. MODUL University Vienna

15. University of Veterinary Medicine, Vienna

16. MCI Management Center Innsbruck

17. St. Polten University of Applied Sciences

The best cities to study Data Science in Austria based on the number of universities and their ranks are Vienna , Linz , Graz , and Innsbruck .

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The Graduate School Office (GSO) at ISTA provides support, development opportunities, funding and advocacy for current and prospective PhD students.

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Cold and Controlled Molecules & Ions 2024 (CCMI 2024)

Moonstone Seminar Center, ISTA campus

September 2-6, 2024

Ista lecture: catherine dulac (harvard).

Raiffeisen Lecture Hall, ISTA campus

September 30, 2024

Institute colloquium: lisa manning, syracuse university, november 4, 2024.

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19 data-science-phd positions in Austria

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PhD Position (m/f/d) "A Bioinformatics Approach to Analyzing Epistatic Interactions in Enzymes using Long-read Sequencing Data "

The Institute of Biomedical Informatics at Graz University of Technology ( TU Graz) is seeking a highly motivated PhD candidate to join a research project in the field of enzyme engineering.This

PhD position in Edge-Cloud computing at the Department of Computer Science

       ○ Scheduling       ○ Programming languages       ○ Algorithms       ○ Data structures       ○ Software engineering    Expert programmer:       ○ Java       ○ At least one other programming language    Practical

University Assistant ( PhD position)

The Working Group Coupled Human Landscape System: Risk & Resilience at the Department of Geography, University Innsbruck (Austria) is seeking candidates for a PhD POSITION (F*M) Interactions

Coordinator

25 May 2024 Job Information Organisation/Company Universität Wien Research Field Biological sciences » Other Researcher Profile First Stage Researcher (R1) Country Austria Application Deadline 17

PhD position in geo-humanitarian action

Research Framework Programme? Not funded by an EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Information extraction, modelling & communication PhD

24 May 2024 Job Information Organisation/Company PLUS (Paris Lodron University of Salzburg) Department Human Resources Research Field Geosciences Researcher Profile First Stage Researcher (R1

PhD Thesis "Innovative Digitalised Services for Future Heat Pump Systems"

cooperation with Sweden's largest technical university. Hereby, you can apply for a PhD degree at KTH Royal Institute of Technology , ranked 34 in the 2023 QS World University Rankings. Throughout your PhD

Junior Visiting Researcher - Doctoral Candidate 12 - EUTERPE (f/m/d)

enrolled in a PhD program at the Department of Gender Studies at CEU for 48 months earliest from September 1, 2024. The first max. 25 months of their studies will be financed from the EU-funded Doctoral

Senior Scientist (Doctorate/ PhD )

24 May 2024 Job Information Organisation/Company University of Innsbruck Department Faculty of Mathematics, Computer Science and Physics Research Field Computer science Researcher Profile Recognised

24 May 2024 Job Information Organisation/Company University of Innsbruck Department Faculty of Biology Research Field Biological sciences Researcher Profile Recognised Researcher (R2) Country

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Studying at the University of Innsbruck

Phd and doctoral programme.

  Deadlines and Admission periods   Admission and documents required for admission   Tuition fee   Forms   Contact & Information

PhD programmes / doctoral programmes are standard study programmes designed to further develop students’ ability to carry out independent scientific work. Building on the knowledge and skills taught in diploma and master’s programmes, they aim to educate and support the next generation of researchers and scientists. In order to be admitted to a doctoral programme, students must have completed a relevant diploma or master’s programme at a university or a university of applied sciences or an equivalent study programme. Graduates are awarded the title “Doctor” in line with the respective curriculum .

>> Full range of study programmes

Deadlines and Admission periods

Dates and Deadlines »

During the general admission period you can

• pay the tuition and/or Austrian Students’ Union Fee (incl. insurance)

Online applications  to a PhD/Doctoral Programme can be made at any time throughout the year (applies to EEA citizens). However, the university recommends that students submit their applications during the normal admission periods in order to be able to register for lectures in time. Please be aware that a special admission period applies to non-EEA applicants (May 15th for winter semester, October 15th for summer semester).

From the start of the general admission period until the end of the extension period you can :

• be admitted as a student of another Austrian university to also study at the University of Innsbruck ,
• be admitted to continue a study programme at the University of Innsbruck after having paid the tuition and/or Austrian Students’ Union fee at another Austrian University
• apply for leave of absence ( before the start of term ).

Admission and documents required for admission

EEA 1 Citizens

If you want to start a Doctoral or PhD-Programme you must apply online. Besides of personal data, also required documents are uploaded. The online application and the enrolment in person are possible all year.

If you have already completed a relevant study programme at the University of Innsbruck you can apply for admission via the online student platform LFU:online.

Documents required for the online application:

• Notice ("Bescheid") confirming awarding of Bachelor's and Master's Degree
• diploma or master’s programme certificate,
• Academic Transcripts
• Diploma Supplements
• (if necessary) Abstract of Master's Thesis
• curriculum vitae
• valid passport or personal identification
• Passport photograph
• E-Card (if available)

Foreign-language documents require translation into German or English – if applicable with proper certification – and must be uploaded. 

Non-EEA Citizens and Stateless Persons:

If you want to start a Doctoral or PhD-Programme you must apply online. Besides of personal data, also required documents are uploaded.   The online application for the winter semester is possible to 15 May and for the summer semester to 15 October.

It is expressly pointed out that the application documents can only be processed with documents proofing the conclusion of the studies. Intermediate certificates or confirmations, temporary transcripts etc. are not accepted.

Full applications will be reviewed by the Admission Department in the order of arrival. Please take care that the processing of the applications may take some time. In the case of a positive decision, you will get a notice, which you need for enrolling.

Prospective students must enrol in person at the Admission Department with the notification of the selected study programme and the original required documents and copies thereof.

• if necessary proof of German or English language ability  

   Information for students with a foreign school-leaving certificate can be found here .

¹ The EEA (=European Economic Area) comprises the Member States of the EU (= European Union) – Austria, Belgium, Bulgaria, Croatia, Cyprus, Czech Republic, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Ireland, Italy, Latvia, Lithuania, Luxembourg, Malta, Netherlands, Poland, Portugal, Romania, Slovakia, Slovenia, Spain and Sweden – and the signatory states of the EFTA (European Free Trade Association) – Liechtenstein, Iceland and Norway.

Tuition fee

Amendments to § 91 Universities Act means that from the summer semester 2013 there are new rules governing tuition fees at the University of Innsbruck.

There are several different rules that apply to students enrolled in standard study programmes. The criteria used to decide which of these rules is to be applied are the nationality of the person, his/her residence entitlement in Austria, and any connections to Austria according to the Austrian Regulation on Eligible Groups of Persons (“ Personengruppenverordnung ”). Non-degree programme students who are enrolled in individual lectures must pay a standard tuition fee of €363.36 per semester.

All students must pay the Austrian Students’ Union fee.

Degree programme students 1 exempted from paying tuition fees for a designated period:  

• EU/EEA citizens (automatically exempted for paying tuition fees for the regular duration of study),
• students with permanent residency (proof required - online application ),
• students from third countries who are deemed to have a connection to Austria according to the Austrian Regulation on Eligible Groups of Persons (“Personengruppenverordnung”) (proof required - online application ),
• students from third countries who are neither covered by the Austrian Regulation on Eligible Groups of Persons (“Personengruppenverordnung”) nor have a student residence permit (proof required).

Students in any of the abovementioned categories who exceed the regular duration of study by more than two “tolerance semesters” must pay a tuition fee of €363.36 per semester. In individual cases a tuition fee waiver may be granted, meaning that students who have exceeded the regular duration of study by more than two “tolerance semesters” remain exempted from paying the tuition fee.

  1 Degree programme students

Degree programme students 1 from third countries

Degree programme students from third countries who are not covered by the Austrian Regulation on Eligible Groups of Persons (“ Personengruppenverordnung ”), are not subject to an international agreement and are in possession of a residence permit according to § 64 Settlement and Residence Act (NAG) must pay a tuition fee of € 726.72 starting from their first term at university. No reduction of the tuition fee will be granted to these students, even if the tuition fee is paid before the end of the extension period.

1 Degree programme students

Degree programme students 1 from Least Developed Countries

Degree programme students from least developed countries (according to the DAC List of ODA Recipients) are automatically exempted from paying the tuition fee . These students do not need to apply for an exemption. However, please be aware that any change of nationality must be communicated to the university without delay.

Non-degree programme 2 students (regardless of nationality)

Non-degree programme students admitted to attend individual lectures in scientific fields must pay a tuition fee of € 363.36 per semester, regardless of their nationality. There is no increase in this fee, even if payment is not completed before the end of the extension period.

2   Non-degree programme students

Tuition fee waivers and reimbursement

In order for tuition fees to be waived or reimbursed, students must prove that their case fulfils the relevant legal requirements (e.g. working income below the marginal earnings threshold, main person responsible for childcare) and must respect certain deadlines. Application for tuition fee waiver: by 31 October for the winter semester and by 31 March for the summer semester. Application for reimbursement: by 31 March for the winter semester and by 30 September for the summer semester. Information about grounds for granting waivers and reimbursements

Forms and information sheets

  "Meldungsblatt" registration form (enrollment, disenrollment, change of study programme)  

Applications for the tuition fee to be waived or reimbursed must be made via LFU:online :

    written confirmation from a specialist doctor  (illness) 

    formal declaration (childcare)

Leave of absence

  Leave of absence

Contact & Information

Admission Department at the University of Innsbruck       » Innrain 52d/Ground Floor 

Master's and Doctoral/PhD Programmes, Study Programmes UMIT, University Continuing Education Programme »

Admission Foreign Students »

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Consultation on our doctoral programmes

Online, via e-mail or telephone

Online-Infosession

Learn more about the doctorate programmes at the University of Vienna

PhD Orientation Week

https://forschung.univie.ac.at/en/services/events-trainings/doctoral-candidates/phd-orientation-week/

Welcome to the Center for Doctoral Studies

The Center for Doctoral Studies is part of the Research and Career Development Unit and the central contact point for matters related to doctoral education at the University of Vienna. The team of the Center for Doctoral Studies offers consultations about the first steps and requirements of the doctoral programmes at the University of Vienna.

Click here for an overview about our support offer.

PhD Orientation Week 2024

Save the Date: PhD Orientation Week

from October 2nd to October 4th 2024

Prospective PhD Candidates

You are interested in a PhD at the University of Vienna? Here you can find more information about the doctorate and the possibilities the University of Vienna offers. 

Read more here

Doctoral Studies

Here you can find information on our offered Doctoral/ PhD programmes and all about the admission procedure.

Read more here.

PhD Process

Get answers to your questions about the structure of the doctorate, courses and the completion of a PhD Programme.

  News & Events

Öaw doc stipendiat*innen 2024.

28 Nachwuchswissenschafter*innen der Universität Wien erhielten heuer ein DocFellowship der ÖAW. Wir Gratulieren den Stipendiat*innen!

PhD Orientation Days

You are starting your PhD at Univie - then do not miss the PhD Orientation Days from 2 - 4 October.

Admission for summer semester 2024

Admission for summer semester 2024 will be possible from January 8 2024 onwards until end of September 2024.

more events

 PhD-Corner

Tiny tornados for storing data

Sabri Koraltan from the VDSP studies the properties of magnetic textures to develop a new type of magnetic field sensors or data storage devices.

Glowing snail mucus as the future of biomaterials

Sophie Greistorfer from the VDSEE is looking for the key to grasping the fundamental principles of a luminescent biopolymer.

Climate activism must be rewarded

Jana Köhler from the VDS CoBeNe wants to help promote climate- and environmentally-friendly behaviour among the population.

• More PhD-Videos

@public: Stefan Sonntagbauer im Podcast zum Thema Horror

Kulturwissenschaftler Stefan Sonntagbauer im Gespräch mit dem Bohema Magazin.

@Public: Florian Danzinger und Stefan Fuchs zum Grünen Band Europas

Florian Danzinger und Stefan Fuchs vom Department für Botanik der Uni Wien berichten in der Rubrik Wissen & Innovation der "Presse" von ihrer...

Forschungs-Team erhält Grant vom Leibniz Institut für Psychologie

Sandra Geiger, Jana Köhler, Mathew White, Sari Nijssen und Maja Grünzner aus der Abteilung für Kognition, Emotion und Methoden in der Psychologie...

• more news from the PhD-Corner

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Data Science (Master)

 data science - a short introduction, joint venture.

The master's programmes Business Analytics , Data Science and Digital Humanities are a joint venture of the faculties of Business, Economics and Statistics, Computer Science, Historical and Cultural Studies, Mathematics, and Philological and Cultural Studies.

The master’s programme in Data Science aims at providing a practically oriented and scientifically sound education in the field of modern data science. Data science is an essential driving force in today’s digital world. In almost all areas of the economy, large amounts of data are collected and generated. Recently, data-driven methods have also found their way into various parts of the natural sciences and humanities. The task of data science is to gain knowledge from ever bigger volumes of data, which represents added value for the respective area. This requires not only the development of efficient algorithms, but also a basic understanding of the interpretability and reliability of results. A diverse and interdisciplinary competence profile is required, which particularly includes the practical handling of large amounts of data, a solid mathematical and statistical foundation as well as knowledge in the respective area of application. In addition, the rapid developments in data science raise ethical and legal questions. The master’s programme in Data Science at the University of Vienna extensively reflects all these core competencies and puts an emphasis on the interdisciplinary and heterogeneous character of Data Science, which is ensured by means of a specialisation in individual areas.

The degree programme requires knowledge of English language at level B2 (Common European Framework of Reference for Languages).

Further information on the degree programme is available here

Master of Science

Degree Programme Code: 066 645

4 semesters / 120 ECTS credits

Language: English

Selection procedure

Learn more on "Data Science @ Uni Vienna"

Bild Data Science EN

© Universität Wien / Barbara Mair

Admission Procedure

Information about the selection procedure

English language requirements

Information on Previous Studies:

In any case eligible degree programmes at the University of Vienna:

• Computer Science (Bachelor)
• Business Informatics (Bachelor)
• Mathematics (Bachelor)
• Statistics (Bachelor)

Getting started

Orientation course

Orientation in the first semester

Semester planning

Getting Informed

StudiesServiceCenter (SSC) Computer Science

Students' Representatives Computer Science

Study Programme

The study programme consists of the compulsory module groups "Mathematical and Statistical foundations, Optimisation Methods, Machine Learning, Scalable Algorithms, Visual Data Analysis", "Doing Data Science", "Ethical and Legal Issues", "Specialisation in Areas of Data Science" and "Master’s thesis". In the module “Specialisation”, students can specialise in individual areas due to the multifaceted range of courses offered, e.g. in principles of Mathematics, Computer Science and Statistics or in various fields of application ranging from the Natural Sciences to Economics and from the Social Sciences to the Humanities. In order to complete the degree programme, students have to write a master’s thesis and pass a master’s examination.

As the degree programme is instructed in English, a proof of knowledge of English language at level B2 (Common European Framework of Reference for Languages) is required.

Focus on interdisciplinarity

The degree programmes Business Analytics , Data Science and Digital Humanities were designed together. Students of all three degree programmes complete the same course contents to the extent of one semester. The offered courses and the various disciplinary locations of students allow for a very broad interdisciplinary exchange.

Five Concepts

which you will deal with during your studies:

• Mathematical & Statistical Foundations
• Mining Massive Data
• Optimisation
• Visual & Exploratory Data Analysis
• Ethics & Legal Issues

...and many more.

 Overview of the programme structure & topics

Here you find the current offer of courses for this programme to gain better insight into the topics and structure. For more information please click on the respective level.

After Graduation

Graduates receive a sound and broad education in core modules, including algorithmic, mathematical and statistical foundations, the handling of large amounts of data as well as explorative data analysis. Additionally, graduates are familiarised with ethical and legal aspects.

They gain in-depth knowledge in concrete fields of application, e.g. from humanities, language processing, finance, medicine, physics, or computational science.

Thereby, they acquire the basis for a doctoral or PhD programme in Mathematics, Computer Science or Statistics/OR and practical skills which are in great demand on the labour market. For example, graduates are qualified to deal with huge volumes of data, statistically analyse complex data and develop, implement and analyse efficient algorithms for data analysis.

Continuing after Graduation

• Center for Doctoral Studies - everything about doctorcal/PhD programmes at the University of Vienna
• Alumni of the University of Vienna
• Postgraduate Center - postgraduate programmes at the University of Vienna
• Uniport - career service of the University of Vienna

Graduates' Perspective on the Degree Programme

Degree programme in retrospect, graduates ....

• say that this degree programme receives the grade: 2.0 (good)
• rate the level of difficulty as: 3.8 (high)

→ These results are based on feedback from 41 graduates.

* You can find further assessments of the degree programme from its graduates’ perspective in the graduate survey of the   master's programmes in Computer Science and Business Informatics  (in German).

Career entry & paths

• find  employment immediately after graduation  on average.
• earn  an average of  € 3,725  (women) and  € 3,991  (men) gross per month  within three years after graduation .
• work full time at  a percentage of  100 %  (women) and  94%  (men)  within three years after graduation .

*You can find further information on career entry and career paths in the tracking of graduates " Information and Communication Technologies ".

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24 PhD jobs in Austria

Find PhD jobs in Austria here. To have jobs sent to you the day they're posted, sign up for job alerts.

• PhD positions in Vienna (14)
• PhD positions in Villach (4)
• PhD positions in Graz (3)
• PhD positions in Innsbruck (1)
• PhD positions in Krems (1)
• PhD positions in St. Pölten (1)

Other countries

• PhD positions in Belgium (150)
• PhD positions in Netherlands (125)
• PhD positions in Germany (53)
• PhD positions in Switzerland (52)
• PhD positions in Finland (41)
• PhD positions in Luxembourg (26)
• PhD positions in Sweden (20)
• PhD positions in Norway (18)
• PhD positions in France (15)
• PhD positions in Israel (5)

Search results (24)

Junior Scientist (m/f/d) for site-specific channel modelling for 6G (Including a PhD Thesis)

Within our Center for Digital Safety & Security the research field Enabling Digital Technologies is leading in applied 5G and beyond research of advanced reliable wireless joint communication and sensing systems for time sensitive use cases in the...

PhD student (f/m/d) – computational genomics and liquid biopsies

Location: ViennaResearch group:  Sabine Taschner-Mandl GroupWorking hours: full-timeAre you looking to apply your bioinformatic skills to patient single cell data and contribute to science that makes a difference? Then this project is for you!For ...

PhD student (f/m/d) – Deep Learning/Computer Vision/Computational Biology for Bioimage Analysis

Location:  ViennaResearch group: Sabine Taschner-Mandl GroupWorking hours: full-timeAre you looking to put your computational skills to the test? Are you fascinated by cancer biology and using multi-omics data to devise new treatment avenues?Then ...

PhD Position in Fungal Biotechnology

Employment as Project Assistant / 30h, 4 yearsBackgroundThe Biochemistry Working Group at TU Wien focuses on using the metabolic capabilities of microorganisms to produce valuable biochemicals. We want to understand how filamentous fungi are able ...

16 PhD and 11 Postdoctoral Positions in Austria in the Research Field “Metabolic Control of Healthy Aging”

Positions Start Date: March 1, 2025Application Deadline: September 10, 2024We invite exceptional graduates from around the globe to join our interdisciplinary research team within the Cluster of Excellence “Metabolic Control of Aging and Disease (...

PhD position (f/m/d) in Pediatric Cancer Initiation

Are you looking for a PhD project that will combine the cutting-edge human stem cells models, stem cell engineering and multi-omic approaches?In our group we have all of this and even more and  we apply it to the burning questions of pediatric can...

Junior Scientist (m/f/d) for the Development of Sustainable Titanium Alloy Concepts (Incl. the Option for a PhD Thesis)

At the LKR Leichtmetallkompetenzzentrum Ranshofen, we are leaders in the development of sustainable materials and processing technologies. We are the primary contact in this field for industry partners in the automotive, aerospace, space, and rail...

PhD Thesis "Digital Twins for Transportation"

As Austria's largest research and technology organisation for applied research, we are dedicated to make substantial contributions to solving the major challenges of our time, climate change and digitisation. To achieve our goals, we rely on our s...

PhD Thesis “Transport Modelling for Sustainable Mobility”

Junior Scientist or PhD position – Brillouin-active Photonic Integrated Circuitry (f/m/d)

YOUR FUTURE RESPONSIBILITIES We are seeking a motivated individual to join a research project in collaboration with an established industrial partner. This exciting opportunity focuses on exploring the potential of Brillouin-active photonic integr...

PhD candidate / Project Assistant - Cooperation between Silicon Austria Labs Villach and University for Continuing Education in Krems (f/m/d)

YOUR FUTURE RESPONSIBILITIES The advertised position is part of a cooperation between Silicon Austria Lab (SAL) in Villach and the University for Continuing Education in Krems (coordinated and supervised by Prof. Hubert Brückl).  Within the “Magne...

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Data Science. Salzburg. Austria.

"Being more than just a sum of existing subjects, the new field of Data Science provides a modern synthesis of key disciplines, driven by today's research questions, and driving the world of tomorrow."

Since 2021 Going international! After five very successful years in German language, the first Data Science Master's Program at an Austrian university is now offered completely in English, making it even easier to take advantage of our international research and enterprise network. And attracting the brightest minds to Salzburg - a place with superb quality of life (and work): https://www.workinsalzburg.at/en/ Competitive application procedure - see below for how to apply.

Since 2020 the intelligent data analytics (ida) lab salzburg , founded in 2020, offers data science students the opportunity to gain hands-on experience in data science projects. research that is motivated by real life applications. main topic areas at ida are smart analytics, space & mobility, reinforcement learning, as well as biostatistics & big medical data., since 2018 dual program - study data science at the university of salzburg while at the same time working with some of the most attractive employers in salzburg. competitive application process at porsche informatik: https://www.studysmartworksmart.at/ unito uni to unito, what does a data scientist do.

A data scientist is fit in statistics and computer science, a good team player, and s/he doesn't lose the big picture in spite of many details. Therefore, today's data scientist first has to really understand the origins of data from which information is to be extracted. To this end, it is essential to have a good communication basis with subject matter experts from different areas, and to speak a common scientific language. After understanding how the data have been generated, they are analyzed using state-of-the-art statistical techniques and the results are presented in an understandable and clear manner. That is, an arc is drawn from raw data to information, from information to knowledge, and from knowledge to making well-informed decisions. Today's data scientists play a central role in this endeavor. What is a Data Scientist?

Why Data Science?

The term describes a mixture of skills that is and will be in high demand - namely knowledge in statistics, data analytics, business analytics, business intelligence, several areas of computer science, as well as legal and ethical principles. Successful graduates of data science programs have excellent and interesting job prospects. As early as 2012, more than 90% of of Fortune 500 companies had started data science initiatives. Existing data science teams of larger companies are being dramatically expanded. Collecting data is done in quasi automatic manner in several technology areas (a.k.a. process mining) and doesn't require large financial resources. However, experts are scarce who can analyze the collected data in analytically sound ways. Therefore, one can safely assume that the demand for data scientists will not drop in the near future, but instead continue to increase. Currently, we are experiencing a revolution of data mining and "big data" into a more and more quantitatively founded science and research area. As a logical consequence, societally relevant ethical and legal questions are increasingly being posed, and quality and reproducibility of the used methods become a focus of attention. Our society urgently needs people who profoundly understand the benefits and limitations of collecting and analyzing data, who are capable to estimate the positive potential of information that is latent in data, and to make it usable for the common good.

Why Data Science in Salzburg?

International students regularly vote for the Wissensstadt (city of knowledge) Salzburg as the most attractive university city in Austria, and one of the top 10 places in Europe for studying. Why? Studying in Salzburg means studying in a fantastic environment. Salzburg is well-known as festival city, as Mozart city, Sound of Music city, as a city with extraordinarily varied and attractive outdoor and cultural offerings. Salzburg's famous old city with an ensemble of baroque buildings has been on the UNESCO world cultural heritage list since 1996. The fortress is among the most visited sights in Austria. After work, one may, for example, go for short or extended jogging or cycling tours either in the Salzach valley or in the surrounding mountain areas. Or you do laps in the nearest public swimming pool which is within 400m walking distance from campus. And the academic environment? Our students say that it is motivating and dynamic. An excellent faculty-to-student ratio and the personal atmosphere in the departments at the University of Salzburg distinguishes our university from the educational mass production at some other locations. Here, quality matters. Among the top scientists who have joined forces for Salzburg's Data Science initiative, there are several (also younger) professors for whom dedicated advising is a top priority. Many of them are responsible for Salzburg being placed on the map of international first class science locations. And, people here love to do research across departmental boundaries. Therefore, Salzburg is an ideal place to do interdisciplinary work.

Admission Requirements

In order to be admitted to the Master's programme in Data Science, students must hold a Bachelor's degree from a recognized domestic or foreign university or post-secondary educational institution. The Bachelor's degree shall be in Computer Science, Mathematics, Statistics, or a field considered equivalent to one of the above. If a student's Bachelor's degree is not deemed equivalent to an acceptable extent, the student may be admitted conditional on a required completion of additional work worth up to 45 ECTS points; these requirements must be satisfied by the end of the Master's program. Only the Rectorate or a member of staff at the University of Salzburg designated by the Rectorate is authorised to make a determination of equivalency and thus whether a student will be admitted.

Application Deadline

Registration is possible for each semester. For current registration deadlines, see. online pre-registration .

Application

All the relevant information (documents, etc.) can be found here: Information about the Data Science MSc at the Admissions Department

Internships

For prospective Data Scientists, it is essential - not only as preparation for the working world, but also in particular to experience first-hand the applicability of learned methods and techniques - to work practically and with real data, and also to understand the processes by which these data are produced. Data Science should not be conducted in abstract academic castles in the air, detached from reality. Therefore, an industrial internship in the course of the Master's program Data Science is not only recommended, but even mandatory. There are cooperations with about 30 companies, public authorities, and other organizations that are interested in Data Science and can often provide internship opportunities themselves.

Mögliche Semesterpläne

University Bulletin (Mitteilungsblatt)

Flexible Elective Module EM7

Data science faculty, selected cooperation partners, media... about data science in general, media.... about data science in salzburg.

Regarding general admissions questions: Admissions Department , University of Salzburg Regarding administrative questions: Andrea Baumgartner , Office, Department of Artificial Intelligence and Human Interfaces, Questions regarding prerequisites, curricular matters, and PhD studies: Arne Bathke , Director, Curricular Committee, Data Science, Regarding the student side of the Master studies, student life in Salzburg and other questions: The team of Data Science Graduate Student Representatives , [email protected]

The contents of our website have been created with the utmost care and to the best of our knowledge. However, we cannot guarantee the accuracy, completeness, and up-to-dateness of the content. The information contained in this website is only intended for general guidance on matters of interest, and therefore, it does not constitute the basis for any legal rights.

Our website contains links to websites of third parties. Since the content of these websites is not under our control, we cannot assume any liability for such external content. In all cases, the provider of the linked website is responsible for any inaccuracies, errors and/or omissions contained in or relating to this information. At the time of linking no infringements of the law were recognizable to us. As soon as an infringement of law becomes known to us, we will remove the respective link immediately.

Major Data Science

From the analysis of industrial tasks to overcoming social challenges: The Data Science major imparts theoretical knowledge and practical skills in dealing with data for a wide variety of application areas that are in great demand on the job market ‒ especially in local businesses.

Data Science in Degree Programmes

Data science research.

Quick Facts

To acquire this specialist knowledge, you can complete the major in Data Science as part of the following master’s degree programmes:

• Computer Science For students in the Master’s Degree Programme Computer Science, the focus on establishing a founded basic knowledge of algorithms is particularly important, as it includes statistical and mathematical modelling as well as machine learning techniques. Programming knowledge is required for the combination of data processing steps and data analysis.  
• Software Engineering and Management For students in the Master’s Degree Programme Software Engineering and Management, the challenges of dealing with large and potentially flowing data are of particular interest. This requires founded knowledge of databases and data management. In addition, business knowledge and skills are another important aspect for successful data scientists.

Depending on the degree programme, the Data Science major includes courses to the extent of 50 to 60 ECTS credit points.

Content of the Major

Data science is the processing and management of data, deriving insights directly from data and making predictions based on data. The types of data processed can vary greatly depending on the field of application and range from ordinal, time, image, text and graph data, and more. Each data type requires special processing and analysis methods and the size and amount of data sets can also pose a major challenge in data management from a certain extent (keyword Big Data).

Students in the Data Science major learn techniques for understanding data that enable them to choose appropriate modelling or processing methods for any given data set. In addition to analytical approaches, interactive data exploration techniques and visual analytics are also used for manual data analysis.

Lectures in the field of Data Science

For questions on the content of the Major: deansoffice.csbme noSpam @tugraz.at Faculty of Computer Science and Biomedical Engineering

For questions about admission: study noSpam @tugraz.at

Research Areas

Data science is unique it that it requires an understanding not only of data, but also of models and management. This also makes data scientists highly sought after people in all the sciences, because looking out for ways of improving existing methods and finding new techniques tailored to novel use cases are often related to specific types of data.

Furthermore, issues such as fairness and the protection of privacy are of the greatest relevance and play an increasingly central role in today’s society, both in the pure sciences and in their practical implementation.

Research Groups

At TU Graz, research is conducted in 16 research groups in the field of Data Science:

• International Business Group (IBG)  
• Cognitive & Digital Science Lap (CoDis) 
• Working, Learning & Technology  
• Learning Analytics & Knowledge Services (LAKS) 
• Data Management for Data Science Lab (DAMS Lab) 
• Immersive Environments 
• Game Lab Graz (GameLab) 
• Social Computing 
• Computational Social Science Lab (CSS Lab) 
• Information Visualisation 
• Visual Analytics 
• Web Science & Engineering 
• Knowledge Discovery  
• Science Technology & Society Unit (STS) 
• Open & Reproducible Research Group (ORrG)

Graz University of Technology Rechbauerstraße 12 8010 GRAZ AUSTRIA Phone: +43 316 873 0 Fax: +43 316 873 6009 E-Mail: info noSpam @tugraz.at www.tugraz.at Campus map Opening hours: 6 am – 8 pm

Service points

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Campus Inffeldgasse Inffeldgasse 25D Phone: +43 316 873 6580 portier.inffeld noSpam @tugraz.at

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7 Best Universities in Australia to Study Ph.D. in Data Science

Pursuing a doctorate in Australia allows graduate students to immerse themselves in academic excellence and a vibrant cultural environment. Thanks to the country’s excellent universities and thriving research communities, having a Ph.D. can pave the way to many opportunities for a learner in their future.

Moreover, there is a rising need for data scientists worldwide because of the progressing technology and the ever-changing area of data science as a study field. That’s why studying this in its doctorate program can provide more groundwork for those who want to work in data science-related careers.

Moreover, a Ph.D. in Data Science is testimony to deepened knowledge in the field that is producing the most lucrative jobs in the world right now. Getting this specific degree in Australia, where some well-known universities are, is a good idea. This article has listed some of the seven best institutions in this country that offer this degree, so make sure to read carefully.

Top Schools Offering Ph.D. in Data Science Programs in Australia

1. monash university.

• Ph.D. Program | Tuition Fees | Scholarships

There’s hardly any global ranking where Monash University doesn’t rank among the top 100. The public research institution was established in 1958 and has a student population north of 86,000. Two of its largest campuses are located in Melbourne, in the suburbs of Clayton and Caulfield, while several others lie across the state of Victoria.

At Monash, students can attain a Ph.D. in Data Science in Australia by developing a research problem within the field that the Faculty of Information Technology approves and then independently investigating it. A supervisory team consisting of at least two supervisors will support the student throughout the program.

Students will undertake compulsory coursework that covers advanced training in IT research methods. The standard duration of the Ph.D. program is four years in full-time format and eight years in part-time format. It takes place at the Clayton and Caulfield campuses.

2. University of Sydney

The University of Sydney is the oldest institution in Australia, beginning its journey in 1850. Its main campus occupies around 178 acres of land in the inner-west Sydney suburbs of Camperdown and Darlington. QS World Rankings 2022 ranks the school first in the country and fourth in the world for graduate employability. Moreover, it is the alma mater of two Nobel laureates and seven Aussie prime ministers.

The university’s Faculty of Engineering allows students to earn a Ph.D. in Data Science in Australia by submitting a thesis that is an original contribution to the field of data science. Students will have access to two research centers: the Centre for Distributed and High-Performance Computing and the UBTECH Sydney Artificial Intelligence Centre. The Ph.D. program in Australia is available in full-time study mode and ideally takes three years to complete.

3. RMIT University

RMIT University is a Melbourne-based public research institution with nearly 87,000 students. It was founded as a night school in 1887 but had to wait more than 100 years to become a full-fledged university in 1992. According to QS World Rankings 2022, it is seventh in Australia and is in the top 100 in the world for graduate employability.

One of the many research areas at the university’s Ph.D. in Computer Science program is data science and analytics. Doctorate students with a topic in a particular research area get to use the RMIT Data Analytics Lab as their research incubator. The program usually takes three to four years in a full-time and six to eight years in a part-time format.

4. University of Melbourne

Established in 1853, the University of Melbourne has its primary campus in the Melbourne suburb of Parkville and other campuses across Victoria. According to Times Higher Education World Rankings 2019, it is the best institution in the country and 32nd in the world. The student population is over 53,000, with 45 percent hailing outside Australia. Multiple Nobel laureates and Australian prime ministers have graduated from this university.

UniMelb’s Melbourne Centre for Data Science allows students to focus their studies in data science in Australia. It provides a nurturing environment where Ph.D. learners across campuses can share their knowledge and ideas about data science through various resources, such as presentations, workshops, masterclasses, etc.

5. University of Technology Sydney

Founded in 1988, the University of Technology Sydney has been recognized by QS World Rankings as one of the top ten young universities in the world. Its main campus is situated in the Sydney suburb of Ultimo.  At UTS, students can pursue a Ph.D. degree, which requires completing three distinct phases.

The program takes four years in full-time study mode and eight in part-time mode. In the first phase, students must validate their candidature by completing a formal test. The second phase sees students develop their research program to guarantee their work is up to par, while the third phase involves preparing and submitting the thesis.

Research students are advised to check in with their supervisor(s) once a month to review their updates. Moreover, various academic disciplines require learners to participate regularly in on-campus or off-campus research projects.

6. University of Queensland

The University of Queensland was founded in 1909. Its main campus, located in St Lucia, Queensland, occupies over 281 acres of land. According to multiple international rankings, it deserves a spot among the top 50 universities in the world. The institution has over 55,000 students, with nearly 40% international students enrolled since 2023, according to UQ’s official statistics .

With UQ’s School of Electrical Engineering and Computer Science , students can earn a Ph.D. in data science in Australia. The program is only available full-time and takes three to four years to complete. Two or more supervisors oversee each student’s work throughout the program. Under their management, you will conduct research, write a thesis of 80,000 words, and pass an oral test.

7. University of Western Australia

The University of Western Australia , which started its journey in 1911, was the sixth institution established in the country. Its main campus lies in the suburb of Crawley in Perth, the capital of Western Australia. Two other campuses are in the Perth suburb of Claremont and the port city of Albany. The public research university has earned the 77th spot in the QS World Rankings 2024.

Like the universities mentioned above, UWA also provides students with the opportunity to earn a Ph.D. in Data Science through an independent, supervised research program. The program is undertaken after a research topic has been mutually agreed upon by a student, their supervisor, the head of the Physics, Mathematics, and Computing, and the Board of the Graduate Research School. It is available in full-time and part-time study modes, with a four-year duration for full-time students.

In conclusion, a Ph.D. in data science from an Australian institution provides a one-of-a-kind opportunity to get a quality education and experience a diverse culture in one setting. Thanks to the increasing demand for this field, your career and research advancement opportunities will always be present. So, if you want to pursue data science in Australia, consider the universities we listed below and start your application as soon as possible!

We hope this article about the top universities in Australia with the Ph.D. in Data Science was helpful. Make sure also to check out our Study in Australia page for learning opportunities in the country and the Available Programs for International Students for some of the currently open courses around the world!

About the Author: Hyun Lee

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Master - Data Science

The goal of the Master's programme in Data Science at the University of Vienna is to provide a practically oriented and scientifically sound education in the field of modern data science. Data Science is an essential driving force in today's digital world . Nowadays, large amounts of data are collected and generated in almost all areas of the economy. Recently, data-driven methods have also found their way into various parts of the natural and human sciences . The task of data science is to gain knowledge from ever larger amounts of data, which represents added value for the respective area. This requires not only the development of efficient algorithms , but also a basic understanding of the interpretability and reliability of the results. This requires diverse and interdisciplinary skills, which includes the practical handling of large amounts of data, a solid mathematical and statistical foundation, as well as knowledge in the respective area of application. In addition, the rapid developments in data science raise ethical and legal questions. The Data Science Master's programme at the University of Vienna comprehensively reflects all these core skills, emphasizes the interdisciplinary and heterogeneous character of Data Science and places it above a specialisation in individual areas.

While the masters degree in data science prepares for a doctoral degree in mathematics, computer science, or statistics, it also teaches practical skills, such as the handling of huge amounts of data, the statistical analysis of complex data and the development, implementation and analysis of efficient algorithms for data analysis, which are in great demand in industry.

Duration : 4 semesters

Credits:  120 ECTS points

Degree:  Master of Science (MSc)

• Availability:  40 university places per academic year

Language of Instruction : English

Degree Programme:  

Administered by:  

» Admission

These topics can be expected during your studies including possible focus areas:

• Machine Learning
• Mathematical & Statistical Foundations
• Optimization Methods
• Mining Massive Data
• Visual and Exploratory Data Science

 Data Science – a short introduction

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Details to the curriculum

Graduates of the Master's programme in Data Science receive a sound and broad education in core modules, including algorithmic, mathematical, and statistical foundations, the handling of large amounts of data, and explorative data analysis. In addition, graduates are familiarized with ethical and legal aspects and gain practical experience in concrete application problems. In the elective modules, graduates are introduced to the state of the art of data science in aspects of computer science, mathematics, and statistics. Further, students acquire in-depth knowledge in concrete fields of application, e.g. from humanities, language processing, finance, medicine, physics, or computational science.

• St. Anna Kinderkrebsforschung e.V.
• Posted on: 19 August 2024

PhD position (f/m/d) in Pediatric Cancer Initiation

Job information, offer description.

Are you looking for a PhD project that will combine the cutting-edge human stem cells models, stem cell engineering and multi-omic approaches?  In our group we have all of this and even more and  we apply it to the burning questions of pediatric cancer oncology!  Here is your chance to contribute to science that makes a difference!

Polina Kameneva just established her research group at the St. Anna Children’s Cancer Research Institute (St. Anna CCRI) and currently recruits 2 PhD students interested in research on the intersection of developmental biology and cancer initiation for new projects funded by the Austrian Science Fund (FWF) START grant and private foundation Paradifference.

There are several research projects that aim to investigate the onset of cancer transformation using the human stem cell models engineered to control the acquisition of mutational hits. The lab aims to engineer the cells for mutation initiation and with such tools to uncover what are the very early transformation of the gene regulatory networks in developing cells which reroute them for the normal differentiation path and turn them into the first cancer cells. The group aims to find and characterize the oncogenically vulnerable and resistant cellular states and look for ways to reduce the risk of pediatric cancer initiation. 

Polina Kameneva has a strong background in the developmental biology of peripheral nervous systems and adrenal glands (Kameneva, Artemov et al., Nat.Genet , 2021; Kameneva, Artemov et al., Cancer Cell , 2021; Kameneva, Melnikova et al., Nat.Com , 2022). With this, the initial focus of the projects is going to be on the adrenal gland associated malignancies: pediatric neuroblastoma, and rare pediatric and adolescence tumors pheochromocytoma and paraganglioma.

Find more information about: 

Polina’s research interests  https://ccri.at/research-group/kameneva-group/  

and Polina herself  https://journals.biologists.com/dev/article/150/17/dev202261/326596/Pathway-to-Independence-an-interview-with-Polina   FWF start project:  https://scilog.fwf.ac.at/en/magazine/how-a-mutation-becomes-cancer

As a PhD Student, you will:

• work on ambitious interdisciplinary research projects on modelling pediatric tumor intiation with human stem cell models
• contribute from the start, including planning of experiments, data acquisition, analysis, and presentation of results
• provide thorough and creative thinking that makes these projects a success
• monitor the literature and community resources to keep abreast of latest developments and to identify information, data, and methods to integrate in your own work
• present your research at local seminars and international conferences, write papers, apply for fellowships, and contribute to grants

Your profile

What you bring for this position: 

• Master’s degree in a relevant subject (e.g molecular biology, cancer, genetics, developmental biology) 
• Excellent technical skills: cell culture, human pluripotent stem cells is a plus, molecular biology (gene editing/CRISPR is a plus), immunofluorescence, confocal imaging, image analysis, FACS, familiar with single cell omics and related computational skills is a plus)
• Motivation to pursue an ambitious research agenda
• Enthusiasm, determination, creativity, scientific curiosity and desire to learn
• Ability to work in a team and individually, committed to success of the project with proactive problem-solving attitude
• Excellent verbal and written communication skills in English (German not required)

Does this sound interesting? This is our offer to you: 

• An exciting, multi-disciplinary environment with a strong support for your personal and professional development from your supervisor, team, and peers
• An outstanding working atmosphere in young and dynamic team
• Access to state-of-the-art infrastructure
• Flexible working hours, discounted lunch and other great benefits
• Great location  in the center of Vienna . Vienna ranks as the most livable city multiple years in a row with attractive prices for accommodation, transport, food, and excellent and diverse recreational options.
• An attractive salary package according to the Austrian Science Fund FWF ( https://www.fwf.ac.at/en/funding/steps-to-your-fwf-project/further-information/personnel-costs ) 

The St. Anna Children's Cancer Research Institute (St. Anna CCRI) is located in the heart of Vienna - one of the most important sites for biomedical research in Europe. St. Anna CCRI is a multidisciplinary and internationally networked center of excellence whose goal is to contribute to a sustainable improvement in the cure rates of childhood and adolescent cancers through innovative research and development. Due to the close cooperation between clinic and research, St. Anna Children's Cancer Research offers the ideal environment for cutting-edge research at a high international level and its implementation in clinical practice.

St. Anna CCRI is an equal opportunity employer. We value diversity and are committed to providing a work environment of mutual respect to everyone without regard to race, colour, religion, national origin, age, gender identity or expression, disability, or any other characteristic protected by applicable laws, regulations and ordinances.

Find more information here:   https://ccri.at/

Your application

Your application should contain  all the documents listed below:

• Curriculum Vitae
• Motivation statement – max 200 words ( shorter is not a problem )
• Short research essay – max 1000 words, not counting references ( shorter is not a problem ) for any of the topics:
• Pediatric tumor cell-of-origin: lessons from animal models and single cell omics research
• Why pediatric cancer is different from adult cancer and needs special research efforts?
• What makes developmental cell states potentially competent for pediatric tumor initiation?
• Academic transcripts
• Contact details of two references  

All parts are mandatory! We kindly ask you to submit the motivation statement, short research essay and the contract details as one pdf file.

The application deadline is 15.09.2024 .  The applications will be reviewed on a rolling basis . We aim to fill the positions fast, therefore the interviews will be organized throughout September and in the beginning of October. We are looking forward to your application!

Where to apply

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