Eric and Wendy Schmidt AI in Science Postdoctoral Fellowship
Apply for Schmidt AI in Science Postdoc 2024
- 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.
- New this year: We are now able to expand the scope of this program to include more biological sciences. Research that uses AI methods to understand the basic biological processes, disease mechanisms and propagation (in silico, in vitro and animals) is within program scope.
Note: MIDAS has been, and remains, a strong supporter of data science and AI in other disciplines, including biomedical, translational and healthcare research, and social sciences. However, any research that involves human subjects or focuses on disease prevention or treatment, including veterinary medicine, is out of scope of this particular program. Social science disciplines are also out of scope. We provide postdoctoral training in these disciplines through the Michigan Data Science Fellows programs, the sister program of the Schmidt AI in Science 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 (please refer to the FAQs for complete details 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 AI (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 AI 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 two disciplines.
We recognize that strength comes through diversity and actively seek and welcome both candidates and mentors with diverse backgrounds, experiences, and identities.
The Application Process
- Applicants must apply online.
- An applicant will need to first secure interest from two U-M faculty members who agree to be their Science mentor and AI mentor respectively. See the FAQ for how to find mentors and see a list of interested faculty mentors here.
- An applicant may reach out to any U-M faculty member(s) to inquire.
- If one faculty member agrees to be a mentor, they may work with the applicant together to secure a second mentor.
- If needed, the program team will help identify AI mentors. Please email firstname.lastname@example.org.
- Applicants are encouraged to consult with the mentors extensively about the research statement and career goals before submitting the application.
The Application Package
The application should be one .pdf file with the following components, each prepared with legible formatting, including at least 1-inch margin on all sides:
- The candidate’s CV.
- Six (6) keywords about research plan.
- Brief summary of research project (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 advances in the application of AI in science domains. 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:
- 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 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 approaches to obtaining AI 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 AI 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 AI is critical to both science and society. Applicants should describe their approaches to and focus on responsible AI research. While such issues may be particularly salient with human subjects or societal impacts, all researchers need to take into consideration the effect of flawed data, brittle analyses, and irreproducible results.
- 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 AI in Science 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 facilitate their career development. The mentors should also provide an explicit commitment to providing sufficient research resources and to participate in the overall Schmidt AI in Science program (see “Expectations” above).
- Names and contact information of two or three additional references. The reference letters should be emailed separately, from letter writers, to email@example.com by the deadline.
- Priority deadline: 11:59 pm EST, Nov. 30, 2023. 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 on Feb. 1, 2024.
- 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, 2024, negotiable for special cases.
- Fit with the program: whether the proposed research vision and the specific project align with the Schmidt AIM program scope.
- Candidate qualification: the candidate’s past experience and accomplishments in both AI and domain research, as expressed in their CV, letters of support and reference letters. Equally importantly, 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 AI 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.
For questions, please contact firstname.lastname@example.org.
Online submission only, through our application form.