Postdoc: Symmetries and their Breaking in Deep Learning

Develop a physics-informed theory of neural networks in Nabil Iqbal’s group at the Amsterdam Machine Learning Lab. Possible topics include symmetry breaking in equivariant networks, scaling laws, nonequilibrium approaches to generative models and sampling for many-body quantum physics. Research includes publications and student supervision. The appointment is 38 hours per week for 24 months, preferably from autumn 2027, with gross monthly salary EUR 3,706–5,760 plus holiday and year-end allowances.

Completed or nearly completed PhD in machine learning, computer science, physics, mathematics or a related field; publications, mathematical/programming skills, independent research and professional English. Apply online with detailed CV, motivation, publications and two referees. A knowledge-security check may be part of selection.