PhD Position Probabilistic Inference in Complex Networks

This PhD position focuses on developing principled probabilistic generative models for analyzing network data to learn hidden patterns in complex systems. Candidates will analyze real-world network data from various domains, design efficient algorithms, and work within the Network Architectures and Services Group. Successful applicants will engage in interdisciplinary research involving engineering infrastructures, biological systems, and social networks under the supervision of Dr. Caterina De Bacco.