Eric and Wendy Schmidt AI in Science Fellowship University of Chicago

The University of Chicago:
Physical Sciences Division:
Data Science

Location:

Chicago, IL

Open Date:
Sep 10, 2025

Salary Range or Pay Grade: $87,418

The Eric and Wendy Schmidt AI in Science Fellowship Program at the University of Chicago is seeking scholars who seek to advance and accelerate the adoption of artificial intelligence (AI) in the natural sciences. The rise of AI in science and engineering presents both a remarkable opportunity and a profound challenge to human‑centered modes of inquiry, including not only data analysis, but also the design of experiments, the formulation of new hypotheses, and the revelation of natural laws.

Given the cross‑disciplinary nature of AI research in science, Fellows will be offered freedom and independence in pursuing their AI‑related research, including the flexibility to change or expand their research focus and to work with multiple research groups while at the University.

This program is part of a vibrant and growing AI and science community that includes departments across the UChicago campus as well as Argonne National Laboratory, Fermi National Accelerator Laboratory, the Marine Biological Laboratory, and Toyota Technological Institute at Chicago (TTIC). These partnerships enable and encourage interdisciplinary research partnerships that leverage the unique capabilities and expertise of these laboratories.

Fellows will have the opportunity to pursue original research on significant questions in AI and science. They form a cohort of top scholars across the natural sciences and engineering who are engaging in joint training and research activities. Fellows will receive the training in AI methods necessary for conducting their research. Drawing on the University’s top‑ranked programs, world‑renowned faculty, and vibrant data science ecosystem, this program allows Fellows to engage in field‑defining research.

It is equally important that our Fellows work and grow in an environment that is supportive and focused on community and career development; as such, this program includes lectures focused on communication and professional development, and aims to develop a diverse cohort of well‑rounded scholars pursuing careers across AI in science research. Opportunities for the Fellows to direct many of the program’s activities enable them to build their leadership skills and ensure that activities are well‑aligned with their needs and interests.

Fellows will receive a competitive salary and benefits, generous research funding and travel allowances, and the opportunity to collaborate with partners worldwide. Fellows will be appointed as Research Scientists in the University’s system of record and are afforded PI status for grant applications.

This is a two‑year appointment with the possibility of renewing for a third year. The anticipated start date is on or around September 1, 2026. This position is benefits‑eligible, and information regarding benefits can be found at

Fellows must hold a doctoral degree in the natural sciences, engineering, or a related field completed before the start of their fellowship and earned no earlier than 2021.

Application review for these positions will begin on October 13, 2025, and will continue until positions are filled. Applications must be submitted online through the University of Chicago Jobs website:

The following materials are required:

• Cover letter indicating the candidate’s potential mentor(s) at the University of Chicago, Argonne National Laboratory, Fermilab, or the Marine Biological Laboratory, and briefly describing the candidate’s area of research.
• A 2-3 page (excluding references) research statement describing the candidate’s research contributions, highlighting: the significance and potential impact of their past and planned research contributions in the natural sciences and engineering, a proposal for exploring AI’s potential role in their research, evidence of the candidate’s preparedness for our training program, and evidence of independence and engagement in activities (e.g., research, seminars, coursework) that span traditional disciplinary boundaries.
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