The goal is to develop fast and practical solutions for fundamental algorithmic problems. This involves designing faster algorithms for classical problems in combinatorial optimization (involving graphs, matchings, submodular functions, matroids, etc), and developing new theory relevant to modern machine learning. The mathematical toolkit is based on modern techniques from continuous optimization, and interferes with other interesting theory from convex geometry, probability and numerical linear algebra. See here for a list of related topics: https://www.irif.fr/users/vladu/projects
We seek candidates with a strong mathematical background, and a master's degree in Mathematics or Computer Science.
This position is fully funded. We provide great working conditions and generous travel support.
If you have any questions, do not hesitate to contact Adrian Vladu (vladu@irif.fr ).
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