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reinforcement learning methods can be used to solve multiobjective discrete and combinatorial optimization problems. The goal is to develop new algorithmic approaches that combine ideas from machine learning
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practices Linux OS, Git-based version control Knowledge in combinatorial optimization Experience in implementing machine learning solutions (in particular reinforcement learning) Experience with one or more
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) Machine Learning and Combinatorial Optimization (subject to personal qualification employees are remunerated according to salary group E 13 TV-L) starting at the earliest possible date. The positions are
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in quantum methods for bioinformatics. Topics may include, but are not limited to, solving hard combinatorial optimization problems with quantum methods, quantum-based data structures (e.g. in