Simons Postdoc in the Physics of Learning and Neural Computation

Postdoctoral position at the intersection of physics and machine learning in Alexander Maloney's research group at Syracuse University's Institute for Quantum and Information Sciences, part of the Simons Collaboration on the Physics of Learning and Neural Computation. The position targets researchers who apply physics techniques to the study of artificial intelligence, such as field theory, random matrix theory and statistical mechanics of disordered systems applied to neural networks, with applications including neural scaling laws, phase transitions in neural networks, statistical models of data and physics-inspired architectures.

The group spans physics, mathematics and computer science, with programmes in machine learning, theoretical physics, quantum information and soft condensed matter. Consideration begins December 1, 2026 and continues until the position is filled.

Background in physics or machine learning (pure physics backgrounds interested in moving into machine learning are welcome). Application: cover letter, CV, publication list, research statement and at least three letters of recommendation.