The fellowship will expand upon an engaged, cross-disciplinary AI and science community that includes divisions and departments across the University, including the UChicago Data Science Institute, and UChicago-affiliated Argonne National Laboratory, Fermi National Accelerator Laboratory and the Marine Biological Laboratory. Each fellow will work with mentors, choosing a researcher from a discipline in the natural sciences or engineering and an AI skills expert, and will join a cohort of scholars for career development, training and research activities.
“We have had a renaissance in machine learning in areas such as computer vision and natural language processing, leading to amazing results. But that success doesn't mean that AI can be used off-the-shelf for science,” said Rebecca Willett, professor in the Departments of Computer Science and Statistics, and faculty lead of the new fellowship program. “There are major open questions surrounding how we quantify uncertainty about the outputs of AI systems, how AI can facilitate the design of experiments, and how best to integrate physics-based knowledge with training data. We hope that, by thinking about AI in the context of science and engineering, we will advance the foundations of AI in addition to advancing the natural sciences.”
The UChicago program is open to those who have completed a Ph.D. in the natural or mathematical sciences, engineering or a related field before the start of their fellowship and no earlier than 2018. Applications are now available for the initial cohort starting Jan. 1, 2023, and a second cohort starting in September 2023.
“I’m excited to see the kinds of scholars that apply for this fellowship,” said David Freedman, professor in the Department of Neurobiology and faculty co-lead of the new fellowship program. “We're looking for people that want to do world-class research in the natural sciences, but who can take advantage of and learn the latest in AI skills to accelerate that research. It goes both ways, too, because AI is a field that can also benefit in so many ways from the natural sciences. It's not just looking at AI as a tool, but the interaction of the natural sciences providing inspiration to explain how AI works or develop a new approach.”
The broader Eric and Wendy Schmidt AI in Science Postdoctoral Fellowship, a program of Schmidt Futures, will initially support approximately 160 postdoctoral fellows across nine universities around the world each year to learn and apply AI methods to their research. Each university will select a new cohort of up to 20 fellows annually for up to six years. Universities joining the program will provide advanced AI training, funded research support and professional development opportunities — both to shape research in their own departments and to help build a global network of AI-trained scientists.
“There’s a recognition that artificial intelligence and machine learning have the potential to be transformative in basic research in the sciences,” said Prof. Joshua Frieman, chair of the Department of Astronomy and Astrophysics, and faculty co-lead of the new fellowship program. “We’re now entering a qualitatively new era where it’s just exploding, and it’s clear that it’s going to have vast implications. We would like to accelerate the incorporation of AI and machine learning into basic research and thereby transform how we do research and what kinds of questions we can ask.”
In addition to the University of Chicago, the Schmidt Future fellowship program will also launch at the University of Toronto; Nanyang Technological University; the National University of Singapore; the University of Oxford; Imperial College London; Cornell University; the University of California, San Diego; and the University of Michigan.