Application Process

Program Overview
Application Process
FAQ
Prospective Hosts
Faculty Fellows
The application portal for the 2027 cohort will open on August 17, 2026.
Scientific Scope Program Structure Expectations Eligibility Application Process & Package Timeline Selection Criteria Program Environment Submission Questions

Scientific Scope

This postdoctoral program supports current faculty members at African universities to apply AI methodologies to address significant research questions in science and engineering. AI is defined broadly to include machine learning, robotics, Bayesian inference, and simulation.

This Fellowship accepts applicants seeking to use AI methodologies in the following scientific domains:

  • Biological and biomedical science (*see exclusion criteria below)
  • Earth and environmental science
  • Engineering
  • Physical science and mathematics

*Exclusion criteria: Biological, biomedical, or healthcare research proposals with a focus on developing or improving disease diagnosis, prevention, or treatment are out of scope for this Fellowship. Biological and biomedical research for this Fellowship must focus on basic biological processes and/or disease mechanisms and propagation (in silico, in vitro, or animal models).

The Phase 1 application deadline for the 2027 cohort is October 5, 2026.

The Phase 2 application deadline for the 2027 cohort is November 23, 2026. 

Program Structure

Each African Faculty (AF) Fellow will be in our program for two years, with one year in residence in Ann Arbor, starting in summer 2027. Each Faculty Fellow will receive an annual stipend of $35,000 and medical insurance for their residence at U-M. In addition, the program will provide housing, and cover visa fees and travel costs between U-M and Africa. Each AF Fellow will also receive funding to cover computer and software licenses, travel to research conferences, fees to attend training workshops, and publication of research papers. Upon their return to Africa, each AF Fellow will receive a pilot grant award of $50,000 to carry out their training, research, and impact plan.

Each AF Fellow will have a U-M faculty member as their host. Hosts must be U-M tenure-track faculty, research scientists, or research faculty. These and the program leadership will form an individualized Fellowship Committee for each AF Fellow. The program will provide $40,000 to each faculty host to carry out one joint research project with the AF Fellow while they are in residence at U-M. (These funds may be used to cover host faculty salary [up to a half month of effort], effort for collaborating students, and/or other costs for the project, in accordance with a budget that must be negotiated and approved prior to funds transfer.) All AF Fellows and their hosts will form a close-knit community together with their collaborators, MIDAS postdoctoral fellows, and faculty mentors, as well as the program team, through collaborative learning activities and research collaborations. AF Fellows will work on the U-M campus. They will have space at MIDAS’s postdoctoral program office space and within the research groups of their hosts.

The program will provide opportunities for AI in science training to the AF Fellows, including summer academies for data science and AI methodologies, AI bootcamps, and collaborative learning sessions. Some program funds are available for additional AI and professional training opportunities at U-M, with our partnering organizations, or elsewhere.

Expectations

AF Fellows are expected to successfully implement their research, training and impact plans and actively participate in collaborative learning and other program activities, as well as activities through the African Studies Center. While in residence at U-M, they are expected to spend at least 50% of time in-person at MIDAS’s postdoctoral offices (currently 3520 Green Court, Ann Arbor, MI). In addition, AF Fellows will be expected to develop an Individualized Training, Research, and Impact Plan (I-TRIP) at the time of application and revise and implement it at U-M and at their home institutions. They will also develop research collaboration with U-M and other US-based scientists. When they return to their home institution in Africa, they will be expected to implement the I-TRIP with support from our program and their U-M faculty hosts and collaborators.

The U-M faculty host will be responsible for co-designing and co-leading a one-year research project with the AF Fellow and managing seed funds provided by the program. The faculty host will work with the program team to help the AF Fellow seek AI skill-building opportunities, develop research collaborations with other U-M AI experts and domain scientists, and develop the I-TRIP.  Faculty hosts are also expected to actively participate in the Schmidt AI in Science program activities in MIDAS, including being champions for the program, reviewing applications, and participating in collaborative learning sessions, among others.

Schmidt Sciences may organize research and networking activities and conferences that will bring together AF Fellows and some hosts from across all of their postdoctoral training sites. The AF Fellows and hosts should meet the participation expectations of Schmidt Sciences.

Eligibility

Applicant Eligibility

  • The candidate must either have (1) a primary appointment as a faculty member at a university in Africa, or (2) an appointment in an African research organization where they carry out research in a capacity similar to a university faculty member. 
  • The candidate must have a PhD degree prior to the start date of the Fellow appointment (July 1, 2027). 
  • This program seeks to support early- and mid-career researchers. Therefore, either (1) the applicant’s PhD conferral date or (2) the beginning of the applicant’s first faculty-level appointment start date (whichever came earlier) must have been on or after July 1, 2017, i.e. within ten years of the Fellowship start date. If an applicant’s PhD conferral date or the date of their first faculty-level appointment was on or before June 30, 2017, he or she is not eligible for this program.
  • The candidate’s 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 the candidate’s PhD.)
  • The ideal candidate will have the expertise to address significant domain science and engineering challenges and enable research breakthroughs, including those that are particularly important for Africa. They should also demonstrate interest in acquiring AI skills and implementing them in the proposed research direction.

Faculty Host Eligibility 

Note: Identifying a U-M faculty host in advance of application is not required for this Fellowship. See the “The Application Process and Package” section below. 

Applicants have the option to contact prospective faculty hosts on this list as part of their Phase 1 application. Please note that the following eligibility criteria are in place for faculty hosts: 

  • This Fellowship seeks to foster new collaborations. For that reason, an applicant’s prior faculty mentor, host, or principal investigator (PI) is ineligible to act as a faculty host. 
  • Additionally, MIDAS seeks to cultivate capacity for AI research across the U-M community. For this reason, U-M faculty hosts can support at most one (1) research Fellow at a time across all MIDAS research Fellowships (including the Schmidt Postdoctoral Fellowship, the African Faculty Fellowship, and the Michigan Data Science Fellowship).
  • Prospective faculty hosts may submit letters of support for more than one applicant in a year, but at most one of these will be selected across all MIDAS research Fellowships. Therefore, supporting more than one candidate in a year will effectively eliminate all but one candidate.

Note: All current and prospective mentors are listed in the faculty directory, here. Any mentor or host for the 2026 cohort is ineligible to serve as a faculty mentor/host for any MIDAS research Fellowship for this application cycle. It is advisable that applicants check their prospective host’s eligibility and discuss these requirements with them.

List of Prospective Faculty Hosts

Click here for a list of prospective faculty hosts.

The Application Process & Package

Phase 1: Each applicant will submit an application package that includes the following:

  • The candidate’s CV.
  • An Individualized Training, Research, and Impact Plan (I-TRIP), up to 4 pages, font size 10 and above, that includes
    • A compelling research 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 and engineering. Applicants will have only a page or two (of the 4 pages total) for this part of the I-TRIP.  It is not expected that the application will contain a full-blown proposal with all details in place, full description of related work, and a complete bibliography.  Rather, just a high-level description of the main idea(s) is sufficient.  If applicants have already been in contact with a prospective host at the University of Michigan, applicants are encouraged to consult with them for feedback.
    • A vision of developing AI in science and engineering capacity once they return to Africa. This can be a variety of projects, such as developing an “AI in Science” class for their university, or a workshop for the local research community; organizing regional AI in Science events; developing exchange activities that allow U-M researchers to visit Africa for research collaboration or teaching; working with grassroots organizations/research networks to promote AI for Science. They may build synergy with other organizations, especially the collaborators of our program. The applicants are strongly encouraged to propose what is feasible and important for their institution, their country, and their region. 
    • Qualifications, experiences, or passions that make the applicant particularly suitable for this program.
    • A short list of essential citations used in the research statement may be included within the 4 pages.
  • (Optional for Phase 1) Faculty Host Letter of Support. If an applicant secures the support of a U-M faculty host prior to applying (see “Faculty Host Eligibility” above), the applicant may upload a letter of support from the host. 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 collaborate with the applicant and to support their impact plan. 

Any eligible Phase 1 application that includes a Faculty Host Letter of Support will automatically pass onto Phase 2.  All other eligible Phase 1 applications will be reviewed by U-M faculty members who have expressed interest in hosting. Based on that review process, all eligible applications that receive the support of a U-M faculty host will pass onto Phase 2 (see below). 

Phase 2: Each applicant will collaborate with their U-M faculty host to improve/revise the I-TRIP and submit the following application supplements:

  • The candidate’s CV.
  • AI Keywords: Please list up to 3 keywords describing specific AI methodologies/approaches you will be applying.
  • A Research Tagline: A phrase describing your overall research goals, no more than 8 words. Accepted applicants will have this tagline posted on the program website. 
  • A Research Blurb:
    • A short summary of the applicant’s I-TRIP and goals as a MIDAS Fellow, written in the third person. This should be written for a generalist audience. In other words, people outside of the core science discipline(s) should be able to understand the work and why it’s important. Try to write it with a mix of technical expertise and generalist explanation. 300 words max. 
    • Note: accepted applicants will have this summary posted on the program website. 
  • A revised I-TRIP, based on discussion with their faculty host.
  • Your Three Best Papers: Upload three written works that best reflect your accomplishments and expertise as a researcher. Publications in peer-reviewed journals will be evaluated most highly, but preprints, working papers, public-facing science writing, and other research-related writing are also appropriate. These should be works where you are a primary contributor.
  • A Letter of Support from the faculty host. 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 collaborate with the applicant and to support their impact plan. 
  • A Letter of Support from the applicant’s home institution approving a leave and affirming that the applicant will resume their position upon completion of the program.
  • 2-3 References – contact info. The applicant will be prompted to provide the names and contact information for individuals who can speak to their training, skills, and experiences pertinent to this program. These individuals will be contacted via email to request a letter of recommendation on the applicant’s behalf.
    • Note: On the application portal, Infoready, you are able to send requests for Reference Letters before you submit your final application. It is strongly encouraged that you send reference requests in a manner that gives your Referees a reasonable amount of time to complete your reference before the application deadline.

Timeline

  • Phase 1 applications are due at 11:59 pm EDT on October 5, 2026. All applications received by this deadline will be given full consideration.
  • Phase 2 applications are due at 11:59 pm EDT on November 23, 2026.
  • Acceptance notifications will start in early February 2027.
  • Accepted Fellows will have two weeks to decide whether to accept the offer.
  • The expected start date will be July 1, 2027, negotiable for special cases.

Selection Criteria

  • Fit with the program: The alignment of research, training and impact plan with program scope and goals.
  • Candidate qualification: The candidate’s past research experience and accomplishments, and the candidate’s potential to become a research leader in the realm of AI in science and engineering.
  • 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 the host have carefully thought about the needs for skills development and are committed to it.
  • Potential of impact: The vision, the approach, and initial feasibility of making groundbreaking research discoveries, contributing to the development of an ecosystem of AI in science and engineering research in Africa, and contributing to longer-term research collaboration between African researchers and U-M (and more broadly American) researchers. 

For questions, please contact [email protected].

Program Environment

The University of Michigan leads the nation among research universities in research expenditures and is a national model of a complex, diverse, and comprehensive public research university. Over 100 U-M graduate programs are ranked in the top 10 in the U.S. by U.S. News and World Report, including its AI graduate education. 

The Michigan Institute for Data and AI in Society (MIDAS) is a reputed center of excellence in data science and artificial intelligence (AI). Our mission is to promote advancements in data science and artificial intelligence, and enable their transformative use in a wide range of research disciplines to achieve lasting scientific and societal impact. MIDAS operates a large number of research activities, training programs, and activities in community building and partnership development. 

MIDAS supports research through a number of approaches:

Developing guidance and resources for reproducible, responsible and ethical data science and AI. 

  • Leading strategic research thrust areas, such as the NSF-funded Center for Data-Driven Drug Development and Treatment Assessment;
  • Providing research resources to enhance the U-M research capacity, including pilot funding.
  • Supporting faculty to develop groundbreaking research ideas and secure major grants.
  • Organizing themed research colloquia and the annual data science and AI Summit.
  • MIDAS training activities include two postdoctoral programs as well as summer schools and year-round tutorials for researchers on applications of data science and AI methods in domain research.

More than 750 MIDAS affiliate faculty members come from all schools and colleges at U-M Ann Arbor campus, and from U-M Dearborn and Flint campuses. This makes MIDAS one of the largest, and one of the most scientifically diverse, data science institutes at a US university. The faculty collaborate extensively, with expertise encompassing theoretical foundations and a wide range of data science and AI methodology, and its applications in almost all research areas at U-M. Our community also includes staff scientists and >1000 graduate and undergraduate students in Data Science and related degree programs, and in student-run data science and AI clubs.  

MIDAS promotes a diverse and inclusive data science and AI research community by supporting researchers from underrepresented demographic groups, supporting staff scientists in academia, and collaborating with Minority-Serving Institutions.

MIDAS works with a large number of industry, academia, government and non-profit organizations to ensure that data science and AI research is enabled by real-world data and inspired by real-world challenges, and that research outcomes are translated into products, services and policies for positive social change. Our External Partnership program offers opportunities for joint research and talent recruitment for industry and public-sector organizations. Our Data for Social Good program uses cutting-edge research to support data-informed decision making for our partners, including the City of Detroit, the Native American tribal nations in Michigan, and the US Environmental Protection Agency. MIDAS is a member of the NSF Midwest Big Data Hub and provides leadership in several focus areas. We also work closely with academic data science organizations to foster a broader and collaborative research community and to maximize synergistic impact. We organize the annual Future Leaders Summit that convenes outstanding students and postdocs from around the country to promote responsible data science and AI and foster the next generation of research leaders.

The African Studies Center (ASC) of the University of Michigan (U-M) provides strategic guidance and coordination for Africa-related education, research and training activities on campus and promotes opportunities for collaboration with African partners. The Center serves as a conduit for U-M’s many Africa initiatives from the humanities, sciences, arts, and social sciences to medicine and engineering. The intellectual content and character of the Center’s programs are shaped by the Center’s Faculty Associates, and, where appropriate, students and affiliates. Its programs serve the general public, the scholarly community, University of Michigan faculty and students, Michigan teachers, and interested citizens and organizations.

The core mission of the ASC is to:

  1. Deepen and expand scholarly and educational partnerships between U-M and African institutions
  2. Support exchanges of students, faculty, and staff between U-M and African institutions
  3. Enhance the study of Africa, past and present, within the U-M curriculum 
  4. Connect faculty and students working in/on Africa from all colleges and units on campus
  5. Foster interdisciplinary research to find imaginative solutions to contemporary social, cultural, medical, technological and environmental problems 
  6. Serve as a public resource on Africa and Michigan’s involvement with it for the state and local community

Submission

The application portal for the 2027 cohort will open on August 17, 2026.

Questions

For questions, please contact [email protected] and see the FAQ page.

TOP