About

I am a theoretical physicist. I use the tools of physics, such as statistical mechanics and information theory, to study condensed matter, quantum science, and artificial intelligence. My goal is to provide a unifying understanding of interacting statistical systems in general, together with mechanistic understanding of emergent phenomena in specific cases of wide interest. On the machine learning side, for example, I am interested in the phenomenon of generalization, in the principles behind scaling laws, and in world models that learn physics. On the physics side, I am interested in how light can dynamically induce far-from-equilibrium phases of matter that cannot exist in the static limit, and in how strong interactions could provide realistic pathways to high-temperature superconductivity or stabilize new correlated phases in two-dimensional materials.

When I am not working, you will find me running, meditating, or taking in as much culture as I can.

Bio

John Sous (pronounced “Soos”) is an Assistant Professor of Applied Physics and Physics at Yale University, where he is a member of the Energy Sciences Institute (ESI), the Yale Quantum Institute (YQI), the Institute for Foundations of Data Science (FDS), and the Wu Tsai Institute. Before joining Yale in July 2024, he was an Assistant Professor at the University of California San Diego. Before that he was a Gordon and Betty Moore Postdoctoral Fellow at Stanford University and a Materials Research Science and Engineering Center (MRSEC) Postdoctoral Fellow at Columbia University. He received his Ph.D. in Physics from the University of British Columbia in 2019.

Joining the group

We are looking for ambitious students and postdocs who want to push the frontier of science, on the AI and machine learning side, on the physics side (condensed matter and quantum science), or where the two meet. We want to discover new phenomena and to explain known ones that remain poorly understood. In a nutshell, I want us to make contributions that change how the community thinks about a problem, whether by uncovering a new mechanism, introducing a new concept, or challenging a widely held belief. These are high-risk, high-reward problems, and the sky is the limit.

You do not need to work on both AI and physics. Most members of the group sit mainly on one side. Nonetheless, interactions across the group and interdisciplinary work are always encouraged.

Ph.D. students

Apply to one of Yale’s Ph.D. programs in Applied Physics, Physics, Computer Science, Applied Mathematics, or Statistics and Data Science, and name me as a faculty member you would like to work with. If you apply to Applied Physics, I see your application directly, so there is no need to contact me before applying; I will get in touch to schedule a conversation if there is a fit. If you apply to any other department, please write to me before you apply so that I can point you in the right direction and navigate the process with that department. Current Yale graduate students in any of these programs are welcome to write to me directly.

Postdocs

The group has periodic openings for postdoctoral positions funded directly by the group. If you are interested, get in touch. Several fellowships also bring postdocs to Yale, and I am glad to work with you on an application to any of them: the FDS Postdoctoral Fellowship, the Wu Tsai Institute Postdoctoral Fellowship, the YQI Postdoctoral Fellowship, and the Yale Mossman Postdoctoral Fellowship in Physics.

Contact