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Phd program in machine learning.

Carnegie Mellon University's doctoral program in Machine Learning is designed to train students to become tomorrow's leaders through a combination of interdisciplinary coursework, hands-on applications, and cutting-edge research. Graduates of the Ph.D. program in Machine Learning will be uniquely positioned to pioneer new developments in the field, and to be leaders in both industry and academia.

Understanding the most effective ways of using the vast amounts of data that are now being stored is a significant challenge to society, and therefore to science and technology, as it seeks to obtain a return on the huge investment that is being made in computerization and data collection. Advances in the development of automated techniques for data analysis and decision making requires interdisciplinary work in areas such as machine learning algorithms and foundations, statistics, complexity theory, optimization, data mining, etc.

The Ph.D. Program in Machine Learning is for students who are interested in research in Machine Learning.  For questions and concerns, please   contact us .

The PhD program is a full-time in-person committment and is not offered on-line or part-time.

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Requirements for the phd in machine learning.

  • Completion of required courses , (6 Core Courses + 1 Elective)
  • Mastery of proficiencies in Teaching and Presentation skills.
  • Successful defense of a Ph.D. thesis.

Teaching Ph.D. students are required to serve as Teaching Assistants for two semesters in Machine Learning courses (10-xxx), beginning in their second year. This fulfills their Teaching Skills requirement.

Conference Presentation Skills During their second or third year, Ph.D. students must give a talk at least 30 minutes long, and invite members of the Speaking Skills committee to attend and evaluate it.

Research It is expected that all Ph.D. students engage in active research from their first semester. Moreover, advisor selection occurs in the first month of entering the Ph.D. program, with the option to change at a later time. Roughly half of a student's time should be allocated to research and lab work, and half to courses until these are completed.

Master of Science in Machine Learning Research - along the way to your PhD Degree.

Other Requirements In addition, students must follow all university policies and procedures .

Rules for the MLD PhD Thesis Committee (applicable to all ML PhDs): The committee should be assembled by the student and their advisor, and approved by the PhD Program Director(s).  It must include:

  • At least one MLD Core Faculty member
  • At least one additional MLD Core or Affiliated Faculty member
  • At least one External Member, usually meaning external to CMU
  • A total of at least four members, including the advisor who is the committee chair

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For applicants applying in Fall 2023 for a start date of August 2024 in the Machine Learning PhD program, GRE Scores are REQUIRED. The committee uses GRE scores to gauge quantitative skills, and to a lesser extent, also verbal skills.

Proof of English Language Proficiency If you will be studying on an F-1 or J-1 visa, and English is not a native language for you (native language…meaning spoken at home and from birth), we are required to formally evaluate your English proficiency. We require applicants who will be studying on an F-1 or J-1 visa, and for whom English is not a native language, to demonstrate English proficiency via one of these standardized tests: TOEFL (preferred), IELTS, or Duolingo.  We discourage the use of the "TOEFL ITP Plus for China," since speaking is not scored. We do not issue waivers for non-native speakers of English.   In particular, we do not issue waivers based on previous study at a U.S. high school, college, or university.  We also do not issue waivers based on previous study at an English-language high school, college, or university outside of the United States.  No amount of educational experience in English, regardless of which country it occurred in, will result in a test waiver.

Submit valid, recent scores:   If as described above you are required to submit proof of English proficiency, your TOEFL, IELTS or Duolingo test scores will be considered valid as follows: If you have not received a bachelor’s degree in the U.S., you will need to submit an English proficiency score no older than two years. (scores from exams taken before Sept. 1, 2021, will not be accepted.) If you are currently working on or have received a bachelor's and/or a master's degree in the U.S., you may submit an expired test score up to five years old. (scores from exams taken before Sept. 1, 2018, will not be accepted.)

Graduate Online Application

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PhD Position in Robotic System Integration for Musculoskeletal Robotic Hands

PhD Position in Robotic System Integration for Musculoskeletal Robotic HandsProject backgroundThe future of robotic manipulation lies in the development of systems that closely mimic the complex st...

Doctoral researcher in Dynamic stochastic learning of train dynamics as enabler to highly automated train operation

Doctoral researcher in Dynamic stochastic learning of train dynamics as enabler to highly automated train operationThis project aims at developing a parsimonious and accurate dynamic model of train...


Postdoctoral researcher in Machine Learning and Computer Vision

Reference number ORU 2.1.1-01781/2024The School of Science and Technology is seeking a postdoctoral researcher in Computer Science and Artificial Intelligence for a fixed-term appointment.Subject areaThe subject area for this position is Computer ...

Postdoctoral researcher in Learning and Perception for Autonomous Systems

Reference number ORU 2.1.1-01780/2024The School of Science and Technology is seeking a postdoctoral researcher in Computer Science for a fixed-term appointment.Subject areaThe subject area for this position is Computer Science.BackgroundThe post-d...

Postdoctoral researcher in Neurosymbolic AI

Reference number ORU 2.1.1-01779/2024The School of Science and Technology is seeking a postdoctoral researcher in Computer Science and Artificial Intelligence for a fixed-term appointment.Subject areaThe subject area for this position is Computer ...


PhD Candidate: Integrating Biopsychological Data to Capture Individual Differences at the Donders Centre for Cognition

Employment 1.0 FTEGross monthly salary € 2,770 - € 3,539Required background Research University DegreeOrganizational unit Faculty of Social SciencesApplication deadline 28 May 2024Do you have a strong interest in developing and studying new tools ...


PhD position on innovative metrology techniques for high power laser applications

Job descriptionWe are looking for a PhD-candidate to strengthen our highly motivated and multidisciplinary research team, who will work on the monitoring and sensing of the fundamental physical phe...

PhD Position in Computational Biology: Using Machine Learning to Understand the Immune System

Are you an aspiring data science researcher with an interest in human immunology, causal inference in dynamical systems, and/or computer vision? Would you like to apply AI and machine learning for fundamental research in biology? Then you have a p...


Postdoctoral Researcher, Remote Sensing for Agriculture and Integrated Water-Energy-Land Nexus Management

The University of Oulu is one of the biggest and most multidisciplinary universities in Finland. We create new knowledge and innovations that help to solve global challenges. We offer you an intern...


Postdoc in Machine Learning

Job descriptionWe are looking for a Postdoc in Machine Learning who will conduct research focussed on the modelling, prediction and planning of motions with applications to assistive technologies a...


Doctoral Researcher (Learning and Control for Autonomous Robotics)

Tampere University and Tampere University of Applied Sciences create a unique environment for multidisciplinary, inspirational and high-impact research and education. Our universities community has its competitive edges in technology, health and s...

PhD Candidate In geo artificial intelligence for planetary health

Job descriptionHelp us to further understand the interplay of global environmental change and people’s health by developing and applying cutting-edge geo-data engineering and geo-artificial intelli...


Post-doc position on AI-augmented boundary plasma modelling for turbulent transport simulations in WEST and ITER tokamak

RESEARCHER PROFILE: Postdoc / R2: PhD holders RESEARCH FIELD(S)1: Physics - Computer scienceMAIN SUB RESEARCH FIELD OR DISCIPLINES1: EngineeringJOB /OFFER DESCRIPTION Fusion based on magnetic confinement aims at producing power by using the energy...


PhD researcher Intelligent Wireless Networking on 6G RAN Optimization

Last application date Oct 30, 2024 00:00Department TW05 - Department of Information TechnologyContract Limited durationDegree Master in Computer Science, Mathematics, Artificial Intelligence, or equivalentOccupancy rate 100%Vacancy type Research s...


PhD Positions in Cancer Research

Are you looking for excellent research opportunities for your PhD studies at the forefront of cancer research? The German Cancer Research Center (DKFZ) in Heidelberg invites international students holding a Master’s degree in (molecular) biology, ...


Upcoming PhD Positions at the International Max Planck Research School for Molecules of Life in Autumn 2024

More information for the new call-out will come up during Autumn 2024. Stay tuned!The International Max Planck Research School for Molecules of Life (IMPRS-ML) will have an open call for fully-funded PhD student positions in the areas of biochemis...

PhD Position: Personalized Prediction and Prevention of Dropouts in Digital Biomarker Studies

PhD Position: Personalized Prediction and Prevention of Dropouts in Digital Biomarker StudiesExciting technological advances in wearables and biosensors rapidly transform how we monitor and manage ...


Head of Research Unit – Embedded AI (f/m/d)

YOUR FUTURE RESPONSIBILITIESWe are looking for an experienced research unit head who will serve as leader and promoter of the highest quality, industry-relevant research in the fields of miniaturization of machine learning and signal processing al...


PhD Students

The CISPA Helmholtz Center for Information Security is looking for PhD Students in areas related to:Cybersecurity, Privacy and CryptographyMachine Learning and Data ScienceEfficient Algorithms and Foundations of Theoretical Computer ScienceSoftwar...


Research Associate (Postdoc) in machine learning optimization and FPGA acceleration for 5G/6G physical layer

The University of Luxembourg is seeking to hire a highly motivated and outstanding researcher in the area of machine learning optimization for physical layer applied to satellite communications in its Interdisciplinary Centre of Security and Trust...

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PhD Program

The machine learning (ML) Ph.D. program is a collaborative venture between Georgia Tech's colleges of Computing, Engineering, and Sciences. Approximately 25-30 students enter the program each year through nine different academic units. 

ML@GT manages all operations and curricular requirements for the new Ph.D. Program, which include four core and five elective courses, a qualifying exam, and a doctoral dissertation defense .

See the curriculum overview for more information.

Students admitted into the ML Ph.D. program can be advised by any of our  participating ML Ph.D. Program faculty .

More information about admission to the ML Ph.D. program can be found here .

More information about the program itself, including details on operations and curriculum outlined in the ML Handbook, can be found in the current student resources.

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Machine Learning Career: Pros and Cons of Having a PhD

Vincent Granville

  • September 25, 2021 at 4:30 pm November 28, 2022 at 12:02 pm

It is often said that data science jobs are for seasoned professionals, and many job ads still show a preference for a profile with a PhD, with years of experience. Yet, many corporate employers have been disillusioned about the value that a PhD brings to the company. Likewise, many professionals, especially among those who just completed a PhD and were offered their first job, find the work sometimes unrewarding.

A PhD may command a slightly higher salary initially, and may be required for a position in a research lab (whether private or government-operated). But for many positions, it may not bring an advantage. Corporate work can be mundane and fast-paced, and the search for perfect algorithms is discouraged, as it hurts ROI. In many companies, a solution close to 80% of perfection is good enough, and requires far less time than reaching 99% perfection, especially since the machine learning models employed are just an approximation of the reality. People with a PhD are not well prepared for that.

Here are some of the negative aspects.

  • Even if you pay someone to write your PhD thesis (such services exist), you may spend several years of your life working on your PhD, possibly in a stressful environment, with low pay, delaying buying a home, or getting married. Meanwhile, you see your non-PhD friends ahead of you in their personal life. If you married when working on your PhD, this could eliminate some of these problems.
  • Some recruiters may say that you are over-qualified, that your experience is not really relevant to the job you are applying for (or too specialized), and that adapting to a fast-paced corporate environment might be challenging.
  • If you land a job in the corporate world, you might find it menial or boring. You could be disappointed that the research you did during your PhD years is a thing of the past, not leading to anything else. This is especially true if your hope was to get a tenured position in the academia, but can’t get one despite your very strong credentials, due to the fierce competition. It can bring long-lasting regrets and nostalgia.
  • You may be lacking some coding skills (SQL in particular), which put you at a disadvantage against a candidate with an applied master. Of course, it is always possible and desirable to gain these skills on your own (or via data camps) when working on your PhD.
  • Your salary might not be higher than that of a younger candidate with a master degree and the right experience. Your cumulative wealth over your lifetime may be lower.
  • Some employers (Google, Facebook, Microsoft, Wall Street,  or defense-related companies) routinely hire PhD’s to work on truly exciting projects. Some only hire from top universities and if your PhD was not from an ivy-league,  you will be by-passed. That said, there are plenty of companies that will hire non ivy-league candidates, and I think that’s a smart move. After all, I earned my PhD in some unknown university, and eventually succeeded in the corporate world.

For some, the pros outweigh the cons by a long shot. This was my case. I provide a few examples below.

  • If your PhD was very applied in a hot field (in my case in 1993, processing digital satellite images for pattern detection), you learned how to code, played with a lot of messy data, and even got part-time job in the corporate world, related to your thesis when working on it, then you are up to a good start. In my case, solid funding for the research, and even data sets, came from governmental agencies (EU and others) and private companies (Total, for instance) trying to solve real problems. This adds credibility to your PhD experience. On the downside, my mentor was not a great scholar, but a good salesman able to attract many well paid contracts.
  • If you earned your PhD abroad like I did, it is quite possible that you were paid better than your peers in US. In my case, my salary, as a teaching assistant, was similar to that of a high school teacher. And conference attendance (worldwide) was paid by the university or by the agencies that invited me as a speaker. Coming from abroad is sometimes perceived as an advantage, due to showing cultural adaptation, and in most cases, being multilingual and able to easily relocate in various locations if corporate needs ask for it.
  • You can still continue to do your research, decades after leaving academia. I still write papers and books to this day. The level is even higher than during my PhD years, but the style and audience is very different, as I try to present advanced results, written in simple English, to a much larger audience. I find this more rewarding than publishing in scientific journals, read by very few, and obfuscated in jargon.
  • There are great positions in many research labs, private or government, available only to PhD applicants. The salary can be very competitive.
  • VC funding is usually contingent to having a well-known PhD scientist on staff, for startup companies. So if you create your own startup, or work for one, a PhD is definitely an advantage. Even when I started my own, self-funded publishing / media company (acquired by Tech Target in 2020, and focusing on machine learning), my wife keeps reminding me that I would have had considerably less success without my education, even though you don’t legally need any degree or license to operate this kind of business.


Having a PhD can definitely offer a strong advantage. It depends on the subject of your thesis, where you earned your PhD, and if you worked on real-life problems relevant to the business world. More theoretical PhD’s can still find attractive jobs in various research labs, private or government. The experience may be more rewarding, and probably less political, than a tenured position in academia. It goes both ways: it is not unusual for someone with a pure corporate / business background, to make a late career move to academia, sometimes in a business-related department. Or combining both: academia and corporate positions at the same time.

I wrote an article in 2018, about how to improve PhD programs to allow for an easy  transition to the business world. I called it a doctorship program, and you can read about it  here . I will conclude by saying that another PhD scientist, who earned his PhD in the same unknown math department as me at the same time (in Belgium), ended up becoming an executive at Yahoo, after a short stint (post-doc) at the MIT, working on transportation problems. His name is Didier Burton. Another one (Michel Bierlaire), same year, same math department, also with a short post-doc stint at MIT (mine was at Cambridge University), never got a corporate job, but he is now an happy full professor at EPFL. Also, a Data Science Central intern (reporting to me), originally from Cuba and with very strong academic credentials (PhD, Columbia University, EPFL) got his first corporate job after his internship with us (I strongly recommended him). Despite a mixed academic background in physics and biology, he is now chief data scientist of a private company. His name is Livan Alonso.

About the Author


Vincent Granville is a pioneering data scientist and machine learning expert, founder of  MLTechniques.com  and co-founder of  Data Science Central  (acquired by  TechTarget in 2020), former VC-funded executive, author and patent owner. Vincent’s past corporate experience includes Visa, Wells Fargo, eBay, NBC, Microsoft, CNET, InfoSpace. Vincent is also a former post-doc at Cambridge University, and the National Institute of Statistical Sciences (NISS).

Vincent published in  Journal of Number Theory ,  Journal of the Royal Statistical Society  (Series B), and  IEEE Transactions on Pattern Analysis and Machine Intelligence . He is also the author of multiple books, available  here . He lives  in Washington state, and enjoys doing research on stochastic processes, dynamical systems, experimental math and probabilistic number theory.

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Best Online Doctorates in Machine Learning: Top PhD Programs, Career Paths, and Salary

Machine learning is a rapidly growing, fascinating field dealing with algorithm development that can be used to make predictions from data. The best online PhD in Machine Learning prepares students for a career in this promising field.

The best online doctorates in machine learning offer students a comprehensive education in all aspects of the field. Students are also provided with the opportunity to choose a specialization such as deep learning, natural language processing , or computer vision. Find out in this article what machine learning PhD online degree program best fits you and the machine learning jobs for graduates.

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Can you get a phd in machine learning online.

Yes, you can get a PhD in Machine Learning online. The online learning system has seen rapid growth in many academic fields and has given students the opportunity to virtually access the academic curriculum remotely.

Many online PhD programs in the United States are accredited and designed with working professionals in mind. Online learning is a great way to earn a doctorate without sacrificing your day job, and in most cases, online students can complete their entire academic journey without stepping foot on campus.

Is an Online PhD Respected?

Yes, an online PhD is respected when it is obtained from an accredited institution in the US. A PhD from an unaccredited school is regarded as just an expensive piece of paper by many other academic institutions.

In regard to employment, many companies and organizations respect an online PhD, holding it to the same standard as an in-person PhD. However, some employers prefer in-person degrees and will disregard online degrees. Ensure your potential future employer accepts online degrees as credible education.

What Is the Best Online PhD Program in Machine Learning?

The best online PhD program in machine learning is at Clarkson University in Potsdam, New York. It is regionally accredited by the Middle States Commission on Higher Education and has an excellent reputation within the academic community, a student-to-faculty ratio of 12 to one, and one in five of its 44,000 alumni is a CEO or executive.

Why Clarkson University Has the Best Online PhD Program in Machine Learning

Clarkson University has the best machine learning PhD program not only because it is accredited by the Middle States Commission on Higher Education (MSCHE) but also because of its US News & World Report ranking. MSCHE is a regionally recognized accreditation association that uses a rigorous and comprehensive system for the purpose of accreditation.

Referring to US News & World Report, Clarkson University is ranked 127 for best national universities out of 4000 degree-granting academic institutions in the United States and 49 for best value schools.

Best Online Master’s Degrees

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Online PhD in Machine Learning Admission Requirements

The admission requirements for an online PhD in Machine Learning typically include a master’s degree or Bachelor’s in Machine Learning or a related subject like the field of engineering. Moreover, prepare to submit official transcripts from previously attended postsecondary institutions and GRE test scores.

Additionally, you may be asked to submit three letters of recommendation, a statement of purpose, a CV or resume, and prove your knowledge of calculus and your fluency in computer programming languages like Python and Java. Below is a list of the typical admission requirements needed by distinct schools that offer a machine learning PhD program.

  • Master’s or bachelor’s degree in a relevant field
  • Official transcripts and GRE test scores
  • Letters of recommendation
  • Statement of purpose
  • CV or resume
  • Knowledge of programming and calculus

Best Online PhDs in Machine Learning: Top Degree Program Details

Best online phds in machine learning: top university programs to get a phd in machine learning online.

The top university programs to get a PhD in Machine Learning are at Clarkson University, Aspen University, Capitol Technology University, The University of Rhode Island, and The University of the Cumberlands, among other distinct schools.

This section discusses the properties, requirements, and descriptions of the best universities offering online PhD in Machine Learning programs. We have created this list below to narrow down your school search for these graduate-level in-depth study programs.

Aspen University is a Distance Education Accrediting Commission accredited university. It was established in 1987 as a private for-profit online university offering undergraduate and graduate degrees in computer science, business information systems, and project management.

Aspen University in Phoenix, Arizona is a known member of the Council for Adult and Experiential Learning and is dedicated to supporting adult learners in achieving a professional career in whatever field they desire.

DSc in Computer Science

This doctoral degree teaches students the theory and practical application of computer science in data science, application design, and computer architecture. It contains 20 courses, including artificial intelligence, risk analysis, and system metrics. 

These courses are offered online and aim to impart students with the necessary skills for improving existing technology, as well as evaluating and applying them. It also contains courses that aid doctoral students in carrying out their research dissertations.

DSc in Computer Science Overview

  • Accreditation: Distance Education Accrediting Commission
  • Program Length: 5 years and 7 months
  • Acceptance Rate: N/A
  • Tuition and Fees: $375/month

DSc in Computer Science Admission Requirements

  • Master’s degree
  • Statement of goals
  • Minimum of 3.0 GPA
  • Must know about object-oriented development

Capitol Technology University was founded in 1927 and offers online programs at the undergraduate, graduate, and doctoral levels. The areas of study in which these online programs are offered include business, technology, and the field of engineering.

PhD in Artificial Intelligence

This is a research-based PhD program that offers students the opportunity to conduct research in any field of their choice. Throughout the program, student work must be approved by the academic supervisor. Students are to submit a thesis and give an oral presentation which will be supervised by an expert in the field.

PhD in Artificial Intelligence Overview

  • Accreditation: Middle States Commission on Higher Education
  • Program Length: 2 to 3 years
  • Tuition and Fees: $933/credit

PhD in Artificial Intelligence Admission Requirements

  • Application fee of $100
  • Master’s degree in a relevant field
  • Minimum of five years of related work experience
  • Two recommendation letters

Founded in 1973, City University of Seattle is recognized as a top 10 educator of adults nationwide, as ranked by the US News & World Report for school rankings. It offers online undergraduate, graduate, and doctoral programs designed for working professionals

PhD in Information Technology

The program’s curriculum consists of courses in machine and deep learning. Candidates are given the option to propose their depth of study, which requires approval from the academic director. The program consists of core courses, concentration courses, a comprehensive examination, a research core, and a dissertation. 

PhD in Information Technology Overview

  • Accreditation: Northwest Commission on Colleges and Universities
  • Program Length: Flexible
  • Acceptance Rate: 100% due to open admission policy
  • Tuition and Fees: $765/credit

PhD in Information Technology Admission Requirements

  • A master’s degree from an accredited or recognized institution
  • CV and resume, and three references letters 
  • Proof of English proficiency
  • Interview with admissions advisor
  • State goals related to your academic work

Founded in 1896 to honor Thomas S. Clarkson, Clarkson University offers flexible online degree programs at the undergraduate and graduate levels. It is a research university that leads in technology education. 

PhD in Computer Science

This doctoral program places emphasis on areas such as artificial intelligence , software, security, and networking. Current students are required to complete 36 credits of computer science foundation and research-oriented courses, elective courses, achieve candidacy within the first two years of the program, and propose and defend a thesis.

PhD in Computer Science Overview

  • Program Length: 3 years
  • Tuition and Fees: $1,533/credit

PhD in Computer Science Admission Requirements

  • Complete the online application form
  • Resume, statement of purpose, and three letters of recommendation
  • English proficiency test for international applicants (TOEFL, IELTS, PTE, and Duolingo English Test)

Northcentral University is a private university established in 1996 and is designed for flexibility by offering programs of distance learning for working professionals. It practices a distinctive one-to-one learning system and has a dedicated doctoral faculty.

In this doctorate program, besides writing papers about past research, students are allowed to propose their research. Its curriculum consists of subjects such as software engineering , artificial intelligence, data mining, and cyber security. Through the course, students conduct research and examine real-world issues in the field of computer science.

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  • Accreditation: WASC Senior College and University Commission
  • Program Length: 3 years and 4 months
  • Tuition and Fees: $1,094/credit
  • Master’s degree from an accredited institution
  • Official transcripts
  • English proficiency exam score for international students

Nova Southeastern University was founded in 1964 in Fort Lauderdale, Florida. It offers online graduate and undergraduate courses and conducts a wide variety of interdisciplinary healthcare research. It is home to national athletics champions and Olympians.

This program provides research in computer science. Its format of learning combines both traditional and online instruction designed with consideration for working professionals . Its coursework consists of research in computer science areas, including cyber security, software engineering, and artificial intelligence.

  • Accreditation: Southern Association of Colleges and Schools, Commission on Colleges
  • Program Length: Not specified
  • Tuition and Fees: $1,282/credit
  • Online application and $50 application fee
  • A bachelor’s or master’s degree in a relevant field from a regionally accredited institution
  • GPA of at least 3.20 
  • Official transcripts from all institutions attended 
  • A resume  
  • Essay, and three letters of recommendation

The University of North Dakota was founded in 1883, six years before North Dakota was made a state. Today, it offers several academic programs in undergraduate, graduate, and doctoral fields and is known for conducting research in areas that include medicine, aerospace, and engineering.

This PhD in Computer Science curriculum consists of courses in machine learning, software engineering, applications of AI, computer forensics, and computer networks which benefit students by granting them proficiencies in areas such as artificial intelligence, compiler design, operating systems, simulation, databases, and networks.

  • Accreditation: Higher Learning Commission
  • Program Length: 4 to 5 years
  • Tuition and Fees: $545.16/credit (in state); $817.73/ credit (out of state)
  • Application fee of $35
  • Master’s or bachelor’s degree in engineering or a related science field
  • GPA of 3.0 on a 4.0 scale and GRE test score
  • Official copy of all college and university academic transcripts
  • Statement of academic goals and three letters of recommendation
  • Expertise in a high-level programming language and basic knowledge of data structures, formal languages, computer architecture and OS, calculus, statistics, and linear algebra 
  • English language proficiency

The University of Rhode Island is a public research institution founded in 1892. It conducts extensive research in the field of science. It offers online, on-site, and hybrid programs at the graduate and undergraduate levels, as well as certificate programs.

In this PhD in Computer Science program, students are involved in research geared toward producing new intellectual and innovative contributions to the field of computer science. It offers a combination of on-campus, online, and day and evening classes. It consists of courses in machine learning, artificial intelligence, software engineering, and systems simulation.

  • Accreditation: New England Commission of Higher Education
  • Program Length: 4 years
  • Tuition and Fees: $14,454/year (in-state); $27,906/ year (out of state)
  • An undergraduate degree from a regionally accredited institution in the US
  • A minimum GPA of 3.0
  • All official college transcripts
  • Personal statement
  • An application fee of $65

Founded in 1888 by Baptist ministers in Williamsburg KY, today the University of the Cumberlands offers online master's and doctoral degree programs in the fields of education, information technology, and business.

The program requires 18 credit hours of core courses which include information technology geared toward creating machine learning engineers . Its curriculum focuses on predictive analytics and other skills students need to become experts in cyber crime security, big data, and smart technologies.

Students have the option to specialize in information systems security, information technology, digital forensics, or blockchain technologies. Students will complete 21 credit hours of professional research while working toward a dissertation.

  • Tuition and Fees: $500/credit
  • A master’s degree from a regionally accredited institution
  • TOEFL for non-native English speakers
  • Application fee of $30

Wright State University was first seen in 1964 as a branch campus for Ohio State University and Miami University. It is a Carnegie classified research university and offers research at the undergraduate, graduate, and doctoral levels.

PhD in Computer Science and Engineering

This degree is awarded to students who show excellence in study and research that significantly contributes to the field of computer science and engineering. The degree requirements include an A grade completion of the core coursework in two areas and at least a B in the third. 

Students are to complete a minimum of 18 hours of residency research before taking the candidacy exam, which must be completed with a satisfactory grade. Also, a minimum of 12 hours of dissertation research is needed before the dissertation defense, which has to be approved.

PhD in Computer Science and Engineering Overview

  • Program Length: 10 years time limit
  • Tuition and Fees: $660/credit (in state); $1,125/ credit (out of state)
  • Bachelor’s or master’s degree in a related discipline (computer science or engineering)
  • Minimum GPA of 3.0 if admitted with a bachelor’s degree or 3.3 with a master’s degree
  • GRE general test portion
  • TOEFL score for non-native English speakers
  • Knowledge of high-level programming languages, computer organization, operating systems, data structures, and computer systems design
  • A record that indicates potential for a career in research

Online Machine Learning PhD Graduation Rates: How Hard Is It to Complete an Online PhD Program in Machine Learning?

It is very hard to complete an online PhD in Machine Learning. According to a paper published in the International Journal of Doctoral Studies, there is a PhD attrition rate of 50 percent in the US within the past 50 years. Therefore, the graduation rate for doctorate students is approximately 50 percent.

How Long Does It Take to Get a PhD in Machine Learning Online?

It takes about four years to get a PhD in Machine Learning online, which is fast when compared to a traditional in-person PhD program which may take over seven years to complete. Online PhD programs are accelerated by default, so the curriculum focuses on the major needs of a PhD graduate in the areas of research, thesis, and dissertation.

Students may be able to reduce the time spent pursuing a PhD in Machine Learning by first acquiring a master’s degree in the field. If you choose to pursue a PhD on a part-time schedule as opposed to full-time study, it will significantly increase the time it takes to acquire the degree.

How Hard Is an Online Doctorate in Machine Learning?

Getting an online doctorate in machine learning is very hard, as are most graduate programs. Besides the rigorous research, strict requirements, deadlines, qualification examinations, and dissertations, other challenges may exist, such as limited student connection with the faculty members, isolation, financial issues, and lack of an adequate work-life balance .

Getting a doctorate in any field is not easy. In fact, there is research to suggest that online doctorate students face challenges regarding culture and academia. As a result of these challenges, many students drop out from their PhD programs.

Best PhD Programs

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What Courses Are in an Online Machine Learning PhD Program?

The courses in an online machine learning PhD program include an introduction to machine learning and deep learning, artificial intelligence, statistical theories, data mining , system simulation, computer programming, and software development.

Main Areas of Study in a Machine Learning PhD Program

  • Machine learning
  • Deep learning
  • Artificial intelligence
  • Databases and data mining
  • Statistical theory
  • Software engineering
  • Systems simulation

How Much Does Getting an Online Machine Learning PhD Cost?

On average, it costs $19,314 per year to get a PhD in Machine Learning, according to the National Center of Education Statistics (NCES). However, this figure is not fixed, as the total tuition for a PhD program varies from school to school.

Private institutions generally cost more than public institutions, but there are funding opportunities for PhD students. Some PhD programs may guarantee financial aid for all their students regardless of merit.

How to Pay for an Online PhD Program in Machine Learning

You can pay for an online PhD in Machine Learning by taking advantage of student loans, scholarships, grants, teaching and research assistantships, graduate assistantships, and fellowship assistantships. As a result, most PhD students spend less than the tuition fee displayed on a school’s website.

How to Get an Online PhD for Free

You cannot get an online PhD in Machine Learning for free. However, there are ways to reduce the cost, or get partial tuition discounts and stipends through graduate assistantships, fellowships, scholarships, or grants.

What Is the Most Affordable Online PhD in Machine Learning Degree Program?

The most affordable online PhD in Machine Learning based on cost per credit is at Aspen University in Phoenix, Arizona. It charges $375 per month, which, when multiplied by the 67 months it takes to complete the program, results in a total of $25,125 for the entire program. This is more affordable compared to a school like Clarkson University, which charges $1,533 per credit hour.

Most Affordable Online PhD Programs in Machine Learning: In Brief

Why you should get an online phd in machine learning.

You should get an online PhD in Machine Learning because having a PhD offers you a stronger advantage in terms of employability, salary, and in your career in general that would otherwise be unavailable with just a bachelor’s and master’s degree.

Top Reasons for Getting a PhD in Machine Learning

  • Research opportunities. PhD students get the opportunity to be involved in rigorous and innovative research that may positively impact humanity, add to the world’s knowledge, and improve the lives of others.
  • Expertise development. A PhD is the highest level of academic degree, and as a result, PhD holders have expert-level knowledge in whichever field they acquire a PhD in. However, it is advised to only get a PhD if you are very interested in the field and willing to explore your interest and expand your understanding through cutting-edge research.
  • Access to better jobs. There are lots of bachelor’s and master’s degree graduates in the job market, and earning a PhD will help you stick out from the crowd. A PhD reveals career opportunities that may not be available to bachelor’s and master’s degree grads.
  • Networking opportunities . During a PhD program, students are in contact with top lecturers and academic experts by attending guest lectures, conferences, seminars, and workshops. Students can network with colleagues and classmates, which helps put them in a good position after their academic journey.

Best Master’s Degree Programs

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What Is the Difference Between an On-Campus Machine Learning PhD and an Online PhD in Machine Learning?

The difference between an on-campus machine learning PhD and an online PhD in Machine Learning is primarily the mode of learning. Online PhDs are as rigorous and effective as their on-campus counterparts.

However, there may be some slight differences between the two in terms of cost, schedule, quality, and funding. Some of the differences that may exist are discussed below.

Online PhD vs On-Campus PhD: Key Differences

  • Affordability. An online PhD is more affordable compared to the traditional on-campus alternative. An on-campus PhD can cost as much as $30,000 per year, while an online PhD may be as low as $20,000 per year.
  • Flexibility. Online PhD students have the liberty to conduct in-depth study and research at their own time as opposed to the schedule of an in-person PhD program. Moreover, most online PhD programs don’t have an enrollment date, and some online PhD work is asynchronous, meaning students can take classes from anywhere at their convenience.
  • Quality. Traditionally acquired PhDs are thought to be superior to their online counterparts by some employers and academics, probably due to sentiment. However, the quality of an online PhD is dependent on the research subject, the school’s reputation, and accreditation.
  • Availability of funding. Funding available for online PhD programs may be limited due to some geographical constraints. For example, online PhD students cannot take up teaching assistantship positions unless they are willing to be physically present.

How to Get a PhD in Machine Learning Online: A Step-by-Step Guide

An online machine learning PhD student sitting at a coffee shop table, working on a computer.

To get a PhD in Machine Learning, you need to first apply online to a PhD program. If accepted, you must enroll in the required classes and complete the academic coursework, research, and a series of academic milestones, which include attaining candidacy, passing the qualification examinations, proposing, writing, and defending your dissertation.

To begin your journey to acquiring a PhD in Machine Learning, you first need to apply online to the school of your choice. You also need to fulfill the admission requirements, including possessing a master's or bachelor's degree–depending on the school–in a relevant field, a minimum grade point average, letters of recommendation, and GRE test scores . 

Many online PhD programs require students to take and pass a minimum number of credit hours in core and elective courses. A typical online PhD in Machine Learning program consists of about 70 to 90 credit hours that involve intensive research in a provided or chosen area of concentration. 

Obtaining a PhD in Machine Learning allows an individual to become a world-renowned expert in the field. After completing a rigorous course of study and passing a series of exams, the doctoral candidate would then undertake an original research project that contributes new knowledge to the field. Upon successful completion of the degree, the graduate would be able to pursue a career in academia or industry. 

Examinations are an essential part of any education. They test a student's understanding of the material and help them to learn and remember the information. If you want to earn a machine learning PhD, you must pass the examinations for various core and required courses. Then, you will need to complete and defend your dissertation.

A dissertation is a research paper that is submitted to and defended by a graduate student to earn a graduate degree. To graduate with a PhD in Machine Learning, you are required to write a dissertation on a topic related to machine learning. Your doctoral dissertation must demonstrate your knowledge and understanding of the field of machine learning, as well as your ability to conduct original research in the field.

Online PhD in Machine Learning Salary and Job Outlook

The job outlook for machine learning jobs is 22 percent between 2020 and 2030 , with the number of new jobs expected in this time frame being 7,200, according to the US Bureau of Labor Statistics. The average salary for computer and information research scientists, which is a category that machine learning professionals belong to, is $131,490 per year .

What Can You Do With an Online Doctorate in Machine Learning?

With an online doctorate in machine learning, you can qualify for specialization roles and lead machine learning positions, including senior machine learning engineer and computer research scientist.

Depending on your preferences, you may also opt for a research and academic career path to become a university professor. The list below is a list of the best jobs for PhD in Machine Learning graduates.

Best Jobs with a PhD in Machine Learning

  • Senior Machine Learning Engineer
  • Computer and Information Research Scientist
  • Data Scientist
  • Software Engineer
  • Postsecondary Teacher

Potential Careers With a Machine Learning Degree

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What Is the Average Salary for an Online PhD Holder in Machine Learning? 

The average salary for a PhD in Machine Learning holder is $108,000 per year , according to PayScale’s salary for skills in machine learning. The average salary a PhD holder receives depends on the location and position you apply for.

Highest-Paying Machine Learning Jobs for PhD Grads

Best machine learning jobs for online phd holders.

The best machine learning jobs for online PhD holders are typically high-paying jobs that require advanced-level skills that coincide with the nature of the position they undertake. Below are some typical job titles that online machine learning PhD degree holders assume.

A senior machine learning engineer oversees a team of machine engineers charged with designing and developing effective machine learning and deep learning solutions implemented in machine learning systems.

  • Salary with a Machine Learning PhD: $153,255
  • Job Outlook: 22% job growth from 2020 to 2030
  • Number of Jobs: 33,000
  • Highest-Paying States: Oregon, Arizona, Texas

Computer and information research scientists research and develop new ways of solving complex computing problems and apply existing technology. They work to significantly increase the knowledge in the field of computer science, which will aid in the production of more efficient software and hardware technologies.

  • Salary with a Machine Learning PhD: $131,490

A senior data scientist is responsible for developing data mining and machine learning techniques to solve complex business problems. They identify patterns and trends in large data sets, develop models to improve forecasting and decision making, and effectively communicate data-driven insights to non-technical stakeholders and lead a team of data analysts.

  • Salary with a Machine Learning PhD: $127,455

A software engineer is a professional that develops and maintains software. They work on a variety of software, from operating systems to video games, and may be involved in the development of websites. They must also have an excellent understanding of computer programming languages and be able to solve complex problems.

  • Salary with a Machine Learning PhD: $121,115
  • Number of Jobs: 1,847,900
  • Highest-Paying States: Washington, California, New York

Postsecondary teachers are in charge of lecturing students in colleges and universities. They are also responsible for instructing adults in several academic and non-academic subjects including career, work, and research.

  • Salary with a Machine Learning PhD: $79,640
  • Job Outlook: 12% job growth from 2020 to 2030
  • Number of Jobs: 1,276,900
  • Highest-Paying States: California, Oregon, District of Columbia

Is It Worth It to Do a PhD in Machine Learning Online?

Yes, it is worth it to do a PhD in Machine Learning online. Getting a PhD is not for everyone, as the process will require tremendous effort and discipline, but it can be rewarding. A PhD in Machine Learning online allows you to learn from some of the best minds in the field.

You can also specialize in an area of your choice, such as big data, natural language processing, or deep learning. Specializing in one area for your PhD in Machine Learning allows you to deep-dive into that subject and build doctorate-level expertise.

An online PhD in Machine Learning provides students with the same high-quality education as a traditional PhD but with more flexibility and affordability. You’ll have access to top-notch instructors, state-of-the-art technology, and a thriving online community of experts.

Additional Reading About Machine Learning

[query_class_embed] https://careerkarma.com/blog/machine-learning/ https://careerkarma.com/blog/best-machine-learning-bachelors-degrees/ https://careerkarma.com/blog/best-machine-learning-masters-degrees/

Online PhD in Machine Learning FAQ

Yes, you should get an online PhD in Machine Learning if it is critical for your career prospects. An online PhD in Machine Learning allows you to learn at your own pace and keep your day job while you pursue your degree. In the end, it sets you up for the highest-earning jobs in the machine learning industry , with better pay and a larger professional network.

The type of research you will carry out as a machine learning student includes research in deep learning, neural networks , machine learning algorithms, supervised and unsupervised machine learning, predictive learning, and computer vision. Students will make use of quantitative and experimental methods of research as well as the use of optimal feature selection.

You can choose a concentration for an online machine learning PhD by factoring in your interests, strengths, and career goals. You may also consider recent trends, the average salary of machine learning professionals , or the career options the machine learning industry has to offer when choosing a machine learning concentration.

Examples of online machine learning PhD dissertations include experimental quantum speed-up in reinforcement learning agents, improving automated medical diagnosis systems with machine learning technologies, regulating deep learning and robotics, and the use of machines and robotics in medical procedures.

About us: Career Karma is a platform designed to help job seekers find, research, and connect with job training programs to advance their careers. Learn about the CK publication .

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The AI explosion has made machine learning jobs hot commodities. But do you really need a Ph.D. to get one?

  • Companies are hiring machine learning engineers as they seek to grow their  AI talent  pools.
  • While some say the role requires a Ph.D., others say it doesn't need an advanced degree.
  • One engineer even considers having a Ph.D. a "red flag." 

Insider Today

Companies are vying to hire the best machine learning engineers — some for salaries well over six figures — as they scramble to staff up as the AI sector booms. Many of these jobs ask for the applicant to have a Ph.D.

But earlier this week, members of the tech community pushed back on X, formerly Twitter, about whether an advanced computer science degree is really necessary for landing a coveted machine learning role.

"I don't wanna get a Ph.D. but wanna work as a Machine Learning Engineer," an X user wrote, kicking off a debate. "Dilemma of the Century."

I don't wanna get a PhD but wanna work as a Machine Learning Engineer. Dilemma of the Century — Tanay Mehta (@serious_mehta) January 23, 2024

In perhaps good news for the original poster, many who replied don't see not holding a doctorate as a barrier to entry.

In fact, Cristian Garcia, a machine learning engineer who works at Google's DeepMind AI division, wrote on X (in a post that was later deleted) that "A Ph.D. is an overkill or even red flag for an ML Engineer Role (IMO)."

Garcia, who says he doesn't have a college degree and is self-taught in machine learning, told Business Insider that Ph.D. programs don't always teach DevOps , data cleaning, data engineering, and skills related to backend work that are typically required to do the job.

Related stories

"Knowing machine learning alone is far from enough," Garcia told BI. "In other words, the actual job is related to ML only tangentially."

A different X user, who claims to have a Ph.D. in computer vision, wrote that recruiters who see "Ph.D." in a job applicant's résumé might think the candidate lacks industry experience — and that they're too expensive and theoretical.

One respondent said a doctorate is only relevant for research, not machine learning engineering. Another even suggested that companies that list a Ph.D. as a hard requirement are most likely looking for researchers instead — "or don't know what they're looking for."

But not all techies think an advanced degree is unnecessary. An X user who claims to be a grad student in computer science said Ph.D. students can bring an innovative approach to real-world problems, which could be an asset to their employers.

The discussion comes as employers and would-be workers assess which skills and education are most useful as the AI job market booms. Recruiters at tech companies big and small have said that job applicants applying for AI-related roles don't necessarily need advanced STEM degrees to be hired.

Chris Foltz, the chief talent officer at IBM, previously told BI that when hiring for AI roles, the tech giant focuses on "prioritizing skills and experiences" over "traditional degrees" if candidates can demonstrate their AI knowledge.

Similarly, Nvidia's vice president of global recruiting Lindsey Duran said that applicants from non-traditional backgrounds can stand out if they can clearly emphasize their career milestones, leadership capabilities, and the impact of their past projects.

Alex Shapiro, the chief people officer at Jasper AI, an AI startup, even said that employees with less conventional backgrounds may, at times, be more attractive to hire than those with technical degrees.

One X user's response to the original post pointed out that a Ph.D. is just one way to become a machine learning engineer. And one other suggests, " Try at a startup, they'll take the risk" on someone without a Ph.D.. Then "break into a good company with that experience under your belt."

On February 28, Axel Springer, Business Insider's parent company, joined 31 other media groups and filed a $2.3 billion suit against Google in Dutch court, alleging losses suffered due to the company's advertising practices.

Watch: An AI expert discusses the hardware and infrastructure needed to properly run and train AI models

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PhD Studentship: IMPACT-RISE: Infrastructural Surrogate Modelling Using Physics-informed and Interpretable Machine Learning for Community Resiliency and Sustainability Evaluation

University of exeter - ese.

Department of Computer Science, Streatham Campus, Exeter,

The Department of Computer Science at the University of Exeter is currently accepting applications for a fully funded PhD studentship, with a negotiable enrolment date open until January 2026 or earlier. For eligible students the studentship will cover Home or International tuition fees plus an annual tax-free stipend of at least £18,622 for 4 years full-time, or pro rata for part-time study. 

Project Description

The IMPACT-RISE project is a pioneering initiative that seeks to revolutionize the field of community resiliency and sustainability analysis through a machine learning (ML) and explainable artificial intelligence (XAI) outlook. The project marks a significant advancement in improving public safety against both low-probability high-impact events and high-probability events with long-term impacts. It focuses on the development of state-of-the-art infrastructural surrogate models using physics-informed and interpretable ML techniques. Our aim is to comprehensively analyse and mitigate the risks posed by diverse extreme events, both natural and anthropogenic (including earthquakes, floods, storms, climate change), on built environment. The primary goal is to enhance our understanding and predictive capabilities, thereby improving decision-making processes to effectively reduce the impact of these hazards on infrastructure systems.

Central to IMPACT-RISE project is the development of data-driven deep learning (DL) based surrogate models that simulate the complex behaviours of infrastructure systems under conditions posed by various hazards (occurring independently and concurrently). These models will be trained while appropriately infusing physics (such as structural dynamics), ensuring not only high accuracy but also enhanced interpretability – a crucial factor for decision-makers in risk management and emergency response. To further boost the interpretability of the DL based surrogate models, principles of explainable artificial intelligence (XAI) will be integrated for a deeper understanding of the models' decision-making processes. Working on the project involves the meticulous collection, development, and analysis of diverse infrastructural and hazard related data sets, ranging from historical incident records to real-time infrastructural sensor data, community maps, and more. Furthermore, the project requires augmentation of real recorded data with simulation data obtained through structural finite-element modelling and analyses.

IMPACT-RISE project aims to provide accurate, reliable, and accessible models, thereby playing a pivotal role in fortifying community resilience and sustainability against various hazards. These innovative tools will be instrumental in pinpointing vulnerabilities, optimizing resource distribution, and crafting effective emergency response plans. IMPACT-RISE is grounded in collaborative effort, bringing together a diverse team of specialists in machine learning, civil engineering, and risk analysis. We are committed to align our models with the practical realities and unique challenges of different communities. Through this integrated and cooperative approach, IMPACT-RISE is set to establish new standards in community protection and infrastructure resilience, confronting the diverse challenges of the 21st century with advanced technological solutions and strategic insights.

The project is open-ended and offers flexibility, inviting applicants to suggest their unique ideas that align with the overarching theme and objectives of the initiative.

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PhD position in the field of Quantum Machine Learning (Prof. A. Lucchi, Dr. Stefan Woerner and Dr. David Sutter)

Academic Positions

Job Information

Offer description.

The University of Basel (Prof. Aurelien Lucchi) and IBM Research Zurich (Dr. Stefan Woerner and Dr. David Sutter) are seeking applications for a PhD position in Quantum Machine Learning. This position offers an exciting opportunity to work on cutting-edge research projects at the intersection of quantum computing and machine learning. Potential topics for the position include developing the next generation of quantum deep neural networks and developing new training algorithms with convergence guarantees. About the University of Basel: The University of Basel is a research university located in Switzerland. It is one of the oldest universities in Europe, with a long history of excellence in natural sciences. The university has a strong focus on interdisciplinary research and collaboration, with a wide range of research groups and institutes across different faculties. The position is offered in the Department of Mathematics and Computer Science. About IBM Research - Zurich: The IBM Research Laboratory in Zurich, Switzerland, is part of IBM's research division, which employs 3000 individuals at twelve research laboratories worldwide. It is the largest industrial IT research organization in the world. Cutting-edge research and outstanding scientific achievements – most notably two Nobel Prizes – are associated with the Zurich Laboratory. Ideal starting date: second half of 2024. Your tasks include:

  • Conduct research in the field of applied mathematics and computer science
  • Write research papers, articles, and present results at leading international conferences. We publish in peer-reviewed machine learning conferences (ICML, NeurIPS, etc. ), in quantum conference avenues (QIP, TQC, IEEE QCE, etc.), and in quantum journals (Nature, PRL/PRX, Quantum, etc.).
  • Interact with national and international teams of mathematicians and computer scientists

Position available starting in the second half of 2024 (position may begin later based on agreement). The position will be primarily based at IBM Research in Zurich (with frequent visits to Basel). Applicants should hold a Master's degree in mathematics, theoretical physics, or computer science (or comparable). You should have several of the following skills:

  • Quantum information theory (theoretical aspects, algorithms, etc)
  • Machine learning
  • Optimization
  • Software engineering (coding in python, Qiskit, etc)

Additional requirements include: outstanding academic record, very strong mathematics background, experience with research is not required but is a plus. Excellent communication skills and fluency in English (spoken and written) are required. We also seek to increase the number of women and other groups in areas where they are underrepresented and therefore explicitly encourage such groups to apply.

  • Close supervision of your Ph.D. research, working with and access to international collaborators
  • A diverse range of tasks in a dynamic environment
  • The possibility to travel to international conferences to meet with distinguished scientists
  • Excellent salary, benefits and working conditions

Application / Contact If interested, please send an application as described below to [email protected] . Your application should be a **single pdf file** containing the following files:

  • Curriculum vitae (including a list of publications if applicable)
  • Scanned transcripts of bachelor's and master's degree
  • Contact information (no direct recommendation letters) for at least two references that can recommend you
  • Your latest thesis (and/or one of your publications if applicable)

You are encouraged to send your application before May 17, 2024. However, there is no deadline for applying, and the position will be open until a suitable candidate is found. If your application is short-listed, we will contact you within three weeks. Due to a large volume of applications, we cannot inform you if your application is not selected for an interview.


Additional information, work location(s), where to apply.

5 Jobs That Will Be in Demand in 2030

Published on may 12, 2024 at 10:28 am by afifa mushtaque in news, 1. machine learning and ai specialists.

Projected Jobs Created: 40%

Machine learning is experiencing unprecedented demand in 2024 as job postings for machine learning engineers are projected to grow by 40% within 5 years in the US alone. The average annual salary for these engineers is $133,336, making it one of the highest-paying jobs in the world . This high demand and excellent earning potential have also increased freelancing opportunities in this area of expertise.

Insider Monkey focuses on uncovering the best investment ideas of hedge funds and insiders. Please subscribe to our free daily enewsletter to get the latest investment ideas from hedge funds’ investor letters by entering your email address below. You can also take a peek at 25 Best Work from Home Jobs and 25 Best Summer Jobs for College Students .

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phd machine learning jobs

AI Fire Sale: Insider Monkey’s #1 AI Stock Pick Is On A Steep Discount

Published on may 1, 2024 at by inan dogan, phd.

Artificial intelligence is the greatest investment opportunity of our lifetime. The time to invest in groundbreaking AI is now, and this stock is a steal!

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Exponential Growth on the Horizon: Forget linear growth – AI is poised for a hockey stick trajectory.

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This isn’t a maybe – it’s an inevitability.

Early investors will be the ones positioned to ride the wave of this technological tsunami.

Ground Floor Opportunity: Remember the early days of the internet?

Those who saw the potential of tech giants back then are sitting pretty today.

AI is at a similar inflection point.

We’re not talking about established players – we’re talking about nimble startups with groundbreaking ideas and the potential to become the next Google or Amazon.

This is your chance to get in before the rockets take off!

Disruption is the New Name of the Game: Let’s face it, complacency breeds stagnation.

AI is the ultimate disruptor, and it’s shaking the foundations of traditional industries.

The companies that embrace AI will thrive, while the dinosaurs clinging to outdated methods will be left in the dust.

As an investor, you want to be on the side of the winners, and AI is the winning ticket.

The Talent Pool is Overflowing: The world’s brightest minds are flocking to AI.

From computer scientists to mathematicians, the next generation of innovators is pouring its energy into this field.

This influx of talent guarantees a constant stream of groundbreaking ideas and rapid advancements.

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I work for one of the largest independent financial publishers in the world – representing over 1 million people in 148 countries.

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Click to continue reading…


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