Scientific Scope
The research of the postdoctoral researchers (Fellows) 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 with clear delineation of 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. Potential applicants whose research is out of scope of the DS Fellows program may consider applying to the Schmidt AI in Science program.
Eligibility
- 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 “Scientific Scope” section above: 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 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.
Expectations
Fellows are expected to successfully implement their research and training plans and actively participate in collaborative learning and other program activities. They are expected to spend at least 50% of time in-person at MIDAS’s postdoctoral office space. In addition, Fellows will be expected to build professional service experience through contributing ~10% of their effort to programmatic activities including training, coordinating research collaboration and building research tools.
Faculty Mentors are expected to devote sufficient time to provide research and career guidance to the Fellows, meet with them regularly, attend Fellowship Committee meetings, and help Fellows seek opportunities for career advancement. They are also required to cover 50% of the Fellows’ salary and benefits; all the costs of the Fellows’ research, including research space, lab facilities, computers, computing resources, data access; travel to research conferences (at least two each year); publication costs; and visa fees. The faculty Mentors may wish to make desk space available in their research groups as well.
Faculty Mentors are also expected to actively participate in the DS postdoc program activities in MIDAS, including being the champions for the program, reviewing applications, and participating in collaborative learning sessions, among others.
Application Process
A list of available faculty mentors will be posted on MIDAS website by September 25. 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. Applicants are encouraged to consult with the mentors extensively about the research statement and career goals before submitting the application. The application link will be available by September 25 , 2024.
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 the proposed research (3 sentences or less). Note: accepted applicants will have this summary posted on the program website.
- Research Statement, up to 2 pages, font size 10 and above, that includes:
- A compelling vision and a plausible approach to achieving that vision. Note that the program seeks to promote research that is transformative and creative, with the potential to spur significant research advances. The statement should also describe the feasibility of the initial scope of the proposed research; and its potential to grow into a sustained research program for an independent research career.
- Qualifications that make the applicant particularly suitable for this program.
- Essential citations used in the research statement should be included in the 2 pages.
- Individualized Development Plan (IDP), up to 2 pages, font size 10 and above, that will include:
- Past accomplishments and current skills that will contribute to the applicant’s success in this postdoctoral training program.
- The data science and AI 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 options;
- Long-term career aspirations, including research, professional development, and career goals, and how this Fellowship will benefit those;
- How the applicant will contribute to the Program.
- Responsible Data Science Statement, up to ½ page, font size 10 and above. Applicants should describe their approaches to responsible data science research. The focus can range 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.
- 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 DEI of the program and to the U-M data science and AI community.
- A Letter of Support from each proposed faculty mentor. This is not a reference letter. Instead, this is similar to a letter of support that is included in a training grant, delineating the applicant’s qualifications, the significance of the research project, the fit with this program, and a plan to mentor the applicant and to support their career development. The mentors should also provide an explicit commitment to providing resources and to participate in the postdoc program (see “Expectations” above).
- Names and contact information of two or three additional references. Please ask the letter writers to email the letters directly to midas-training@umich.edu by the deadline.
Timeline
- Priority deadline: 11:59 pm EST, Nov. 23, 2024. All applications received by this deadline will be given full consideration. Late applications may be considered until all slots are filled.
- Offers will start to be sent out in early February 2025.
- Accepted Fellows will have two weeks to decide whether to accept the offer.
- The expected start date will be between Aug. 1 and Sept. 15, 2025, negotiable for special cases.
For questions about this application, please contact midas-training@umich.edu.
Selection Criteria
- Fit with the program: whether the proposed research vision and the specific project align with the program scope.
- Candidate qualification: the candidate’s past experience and accomplishments in both data science and domain research; the candidate’s potential to become a research leader of the next generation: their willingness to take risks, creativity and originality, curiosity, collaborative spirit, entrepreneurship, and the ability to think big, as reflected in their past accomplishments and proposed plans.
- Research statement: the vision, the approach, and initial feasibility, the potential of making groundbreaking discoveries, the potential of becoming a sustained research portfolio after the Fellow leaves the program.
- Skills development: the candidate’s potential to acquire strong methodology skills for the proposed research and long-term impact in the field; evidence that the candidate and mentors have carefully thought about the needs for skills development and are committed to it.
- Mentors: whether the selection of mentor(s) is appropriate for the research project, the training plan, and career development, as well as consistency among the mentor’s letters and the explicit commitment of the Mentors in participating in the broader program.
- Diversity: Of both fellows and mentors, along multiple dimensions, including demographics and disciplines.
- For University of Michigan internal applicants: whether the proposed research is significantly different from the current research and whether the proposed mentors are different from current ones.
Interested Data Science Mentors
Click here for a list of interested Data Science Mentors
Submission
Online submission only, through our application form.