The aim of the project is to build common representations for assemblies of artificial agents and study their impact on global fitness and efficient resource usage. The project encompasses both engineering and theoretical inquiries. The project started in 2025 and is set to end in 2029.
We are looking for a highly motivated PhD student with background in applied mathematics (machine learning, deep learning) or computer science that has interest in discrete geometry, combinatorial topology and, more generally, the application of geometry and topology to machine learning.