Eric and Wendy Schmidt AI in Science Fellowship 2027: Applications and Eligibility Guide

The Eric and Wendy Schmidt AI in Science Fellowship at the University of Chicago is a postdoctoral research opportunity designed to help scientists incorporate artificial intelligence into research in the natural sciences. The programme is part of Schmidt Sciences’ broader effort to accelerate the use of AI in scientific discovery. The University of Chicago says fellows receive AI training, research support and opportunities to collaborate across its scientific community.

The fellowship focuses on the growing intersection between artificial intelligence, machine learning and scientific research.

According to the University of Chicago, the programme is intended for scholars who want to advance the adoption of AI in the natural sciences. Fellows have the freedom to pursue research questions that combine their disciplinary expertise with AI methods and can work with multiple research groups during their time at the university.

The programme is part of a wider interdisciplinary research ecosystem involving University of Chicago departments and external research institutions including Argonne National Laboratory and Fermi National Accelerator Laboratory.

What the Fellowship Offers

The University of Chicago describes the fellowship as a research-focused programme rather than a conventional taught course.

Successful fellows can expect opportunities to receive:

AI and machine-learning training: Fellows receive training designed to help them apply AI methods to their scientific research.

Independent research: Fellows are given flexibility to develop original research on significant questions involving AI and science.

Faculty collaboration: Fellows can collaborate with University of Chicago faculty and research groups across disciplines.

Research funding: The programme’s main overview states that fellows receive generous research funding and travel allowances.

Competitive compensation: The University of Chicago describes the fellowship as providing a competitive salary and benefits.

Interdisciplinary community: Fellows become part of a broader AI and science research community involving academic and national-laboratory partners.

Research Areas

The fellowship is designed around the idea that AI can transform scientific discovery beyond simply analysing existing datasets.

The University of Chicago highlights potential applications involving data analysis, experiment design, hypothesis generation and the discovery of natural laws.

This makes the fellowship particularly relevant to researchers whose work could benefit from methods such as machine learning, computational modelling, scientific AI and advanced data analysis.

Applicants should be able to explain clearly how AI could strengthen their proposed research rather than simply describing a general interest in artificial intelligence.

Who Can Apply?

The University of Chicago’s application information states that fellows must hold a doctoral degree in the natural sciences, engineering or a related field, earned no earlier than 2014.

The programme therefore targets established researchers and is not a general undergraduate scholarship or entry-level internship.

Applicants should have a strong scientific research background and a proposal showing how AI techniques could contribute meaningfully to their work.

Is Previous AI Experience Required?

One particularly important feature of the programme is that prior experience with AI is not required.

The University of Chicago states that applicants do not need previous AI experience, but ideal candidates should present a clear research proposal explaining what they hope to achieve through AI, what data they intend to use, the approximate size of the dataset, where the data will come from and which new skills they hope to acquire.

This makes the fellowship potentially valuable for scientists who have strong expertise in their scientific discipline but want to develop deeper AI capabilities.

Faculty Mentor Requirement

Applicants should identify a potential University of Chicago faculty mentor before applying.

The official application information asks candidates to contact a potential mentor, discuss research directions and obtain a letter confirming the faculty member’s willingness to serve as a mentor.

This means prospective applicants should think carefully about research fit rather than selecting a mentor simply because of their academic reputation.

A strong mentor relationship should connect the applicant’s scientific expertise, proposed AI methods and intended research outcomes.

Fellowship Duration and Location

The supplied University of Chicago application information describes a six-month fellowship at the University of Chicago, with tentative programme dates from January 4 to June 30, 2027.

The fellowship is based in Chicago, Illinois, and the programme provides support for fellows during their stay.

The university states that the support includes an allowance for travel, housing and living expenses, with additional support potentially available for fellows facing family-care challenges.

Applicants should verify the latest programme terms directly before relying on any particular funding amount or arrangement.

Application Process

The official University of Chicago application page provides an application pathway for the fellowship and identifies the programme contact email as schmidtaiscience@uchicago.edu.

Applicants should prepare a research proposal that demonstrates:

the scientific problem they want to investigate;
why AI is relevant to solving the problem;
what data will be used;
how the proposed AI methods will contribute;
which AI skills they need to develop; and
what scientific outcomes they hope to achieve.

A well-developed proposal should demonstrate a genuine connection between the applicant’s existing expertise and the proposed AI-driven research.

Why the Fellowship Matters

AI is increasingly influencing how researchers analyse data, build models and approach scientific problems. Schmidt Sciences describes the fellowship as part of an effort to accelerate the incorporation of AI into STEM research because adoption remains uneven across scientific and engineering fields.

The University of Chicago similarly argues that AI can affect not only data analysis but also hypothesis development, experimentation and scientific discovery.

For researchers, this creates an opportunity to develop interdisciplinary skills that combine domain expertise with modern computational approaches.

Important Application Update

There is an important distinction between the source initially supplied and the current official University pages.

The original University of Chicago page provided in the prompt currently returns a “No Results Found” page, but the university’s dedicated AI in Science Fellowship website still contains programme and application information. The University’s official application page provides details for the programme with tentative 2027 dates, eligibility requirements, mentor expectations and funding support.

The university’s main fellowship website also currently states that the programme is accepting applications.

Prospective applicants should therefore use the current official fellowship application page rather than relying on an outdated or missing University page.

Final Thoughts

The Eric and Wendy Schmidt AI in Science Fellowship 2027 at the University of Chicago is a specialised opportunity for researchers who want to integrate artificial intelligence into scientific research.

The programme combines AI training, independent research, faculty mentorship, interdisciplinary collaboration and financial support for fellows during their time in Chicago. The official information also makes the opportunity distinctive by stating that previous AI experience is not mandatory, provided applicants can present a compelling research plan showing how AI will advance their scientific work.

Researchers considering the fellowship should focus on research fit, mentor alignment and a clear explanation of how AI can generate meaningful scientific value. The official University of Chicago application information should be treated as the authoritative source for current eligibility, dates and application requirements.

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