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Apply for Michigan Data Science Fellows 2024:

**Applications are now closed.**

Research Themes

The applicant’s research should align with one or more of the following areas.

  • Enhancing Scientific and Societal Impact: Integrating methodologies and tools to enable responsible data science and AI research and enhance its scientific impact; applying data science and AI methodologies and tools to inform policy and promote social good.
  • Measuring and Improving Society: better understanding society through the use of new data types such as text, image, sensor and digital trace data (including social media and other digital transactions).
  • Transforming Health Interventions: enabling the transformation of health interventions through the use of cutting edge data analytics and AI methods.
  • Data science theory and methodology development is within scope of the DS Fellows Program, as long as the applicant clearly delineates how it advances research in one of the three areas listed above.

Please note that there is a sister program at MIDAS, the Eric and Wendy Schmidt AI in Science Postdoctoral Fellowship, which supports postdocs who apply AI methodology to address significant research questions in science and engineering. AI is defined broadly to include machine learning, robotics, Bayesian inference, and simulation. Science and engineering includes mathematical sciences, physical sciences, earth and environmental sciences, basic biological sciences, and engineering. All other disciplines, including biomedical, translational, medical, healthcare research, and social sciences, are out of the scope. Potential applicants whose research theme falls within the Schmidt program and is out of scope of the MIDAS DS Fellows program are encouraged to apply to the Schmidt AI Fellows program.


  • The candidate must have a PhD degree prior to the start date of the Fellow appointment, but within five (5) years.  
  • The PhD can be in any field. (Note the science and engineering domains listed above that are in scope: these apply to the area of proposed work, but not to the field of PhD degree). 
  • It is acceptable for the candidate to already have a postdoc position, whether at U-M or elsewhere (but please see below about U-M candidates). 
  • The candidate should not have had a faculty appointment anywhere that is equivalent to a North American university’s tenure-track position. 
  • The ideal candidate will have training in both data science (at least one sub-area) and the domain discipline.  However, this may not be the case for many candidates. 
    • We require that a candidate have deep expertise in at least one of the two: either data science methodologies or the domain discipline, in conjunction with demonstrated interest in the other.  
    • The key requirement is evidence of excellence and a passion for the proposed research direction at the intersection of the two disciplines.

We recognize that strength comes through diversity and actively seek and welcome both candidates and faculty mentors with diverse backgrounds, experiences, and identities. This is our commitment to doing our part in building a diverse data science and AI research workforce, bringing together diverse perspectives and research approaches, and maximizing the scientific and social impact of data science and AI research.

Individuals already at U-M are eligible to apply if their proposed project AND proposed faculty mentors are different from their current ones. 


  • Fellows are expected to spend at least 50% time of their time at MIDAS. Each Fellow should also spend an appropriate amount of time with their faculty mentors’ research groups (based on agreements between the Fellows and mentors).
  • Fellows are required to actively participate in the collaborative learning activities which are conducted jointly with the Schmidt AI in Science Program Fellows.
  • Fellows are also expected to participate in programmatic activities that can help build their professional service experience. They may choose to participate in training activities as instructors, or organize research connection events, or develop algorithms, tools, research protocols that can be shared with the campus research community. These activities should account for, on average, 5-10% of the Fellows’ effort.

The Application Process

See a list of faculty members who are accepting postdocs. Applicants may reach out to faculty members on the list to seek interest. The candidate and the mentor(s) will then submit the application to MIDAS. The application link became available on Sept. 1, 2023.

Applications will be accepted between Sept. 1 and Nov. 30, 2023.

The Application Package

The application package should be uploaded online as a single .pdf file and should include the following components:

  • The candidate’s CV.
  • Six (6) keywords about the research plan.
  • Brief summary of research project (3 sentences or less). Note: accepted applicants will have this summary posted on the program website. 
  • A Research Statement (up to 2 pages) that includes: 
    • The proposed data science research, including its importance and potential impact; 
    • Qualifications that make the applicant particularly suitable for this program. 
  • Individualized Development Plan (IDP), up to 2 pages, font size 10 and above, that will include:
    • Part 1. Self-assessment: A) Describe past accomplishments will contribute to the applicant’s success in this postdoctoral training program. Describe the skills the applicant will bring. B) Describe the data science expertise the applicant will need to acquire during the Fellowship, and an initial learning plan that may consist of a variety of formal and informal approaches to obtaining data science expertise;
    • Part 2. Career goals: Describe the applicant’s long-term career aspirations, including research, professional development, and career goals, and how this Fellowship will benefit those;
    • Part 3. Objectives: Describe how the Program (including training and participation in a cohort) will benefit the applicant in achieving above outlined goals; 
    • Part 4. Contribution to Program: Describe how the applicant will contribute to the Program.  
  • Responsible Data Science Statement, up to ½ page, font size 10 and above. From the rigor of study design and the explainability of models, to the unbiased use of data and algorithms, and to data sharing and making a research project fully reproducible, responsible data science is critical to both science and society. Applicants should describe their approaches to and focus on responsible data science research.
  • Diversity, Equity and Inclusion (DEI) Statement, up to ½ page, font size 10 and above. Describe how the candidate’s life experiences, past activities or anticipated activities will contribute to the diversity, equity and inclusion of the program and to the U-M data science and AI community. 
  • A Letter of Support from mentor(s). The letter should include a justification of the proposed research and why the mentor and the candidate are a good match, a mentoring plan, and the confirmation that the mentor(s) is committed to providing 50% of the funding if the applicant is accepted to the program. The letter should be included in the application package.  
  • Names and contact information of two or three additional references. Please ask these individuals to email their reference letters to midas-training@umich.edu by 11:59 pm, Nov. 30, 2023.


  • Aug. 30:  The initial Data Science program participating faculty list will be posted online. The list will be updated constantly.
  • Nov. 30, 2023, 11:59 pm EST:  application deadline.
  • Notification: Feb. 1, 2024.
  • Start: Aug. – Sept. 2024.

For questions about this application, please contact midas-training@umich.edu.

Additional Information

Please also read carefully the “For Mentors” section,  which contains comprehensive information about the program and expectations for both Fellows and their mentors.


Online submission only, through our application form.