Opportunities
We have multiple Ph.D. and M.S. student positions available. Self-motivated students with interest in our project are encouraged to contact the faculty shown on the Team for more information about the position.
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Optimization and modern AI are strongly related: On the one hand, a fundamental aspect of contemporary AI is optimization. However, in reality, AI may greatly speed up the resolution of challenging optimization issues. In order to revolutionize chip design, robots, networks, and other high-stakes application domains, we at TILOS want to co-advance contemporary AI and optimization. We also pioneer learning-enabled optimizations. We welcome visiting researchers from the practical front (translating learning + optimization for our core use domains) as well as the foundational front (e.g., optimization in modern ML architectures (including LLMs), federated learning and distributed optimization, ML for (combinatorial) optimization, dynamic decision making, and representation learning).