Simons Postdoc in the Physics of Learning and Neural Computation

Position Description

Syracuse University's Institute for Quantum and Information Sciences invites applications for a postdoctoral position at the intersection of physics and machine learning in Alexander Maloney's research group, as part of the Simons Collaboration on the Physics of Learning and Neural Computation. The anticipated start date is September 2026, but is flexible.

This position is targeted towards researchers who wish to apply physics techniques -- broadly defined -- to the study of artificial intelligence. Potential research areas include the application of field theory, random matrix theory, and statistical mechanics/disordered systems techniques to the study of neural networks. Potential applications include: neural scaling laws, phase transitions in neural networks, statistical models of data, and physics inspired architectures. Given the rapidly evolving nature of the subject, we welcome applicants with broader interests.

The successful applicant will join an exciting theory group that spans physics, mathematics and computer science, with active research programs in machine learning, theoretical physics, quantum information theory, and soft condensed matter physics.

This position is open to candidates with either a physics or a machine learning background, and also to candidates with a pure physics background that are interested in switching into machine learning.

Consideration of applications will begin on December 1, 2026 and continue until the position is filled.

Application Instructions: Applicants should submit a cover letter, a curriculum vitae, a list of publications, a statement of research interests and at least three letters of recommendation to this posting on academic jobs online.