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The Department of Mathematics and Computer Science (IMADA) at the University of Southern Denmark, Odense, invites applications for a PhD position in algorithms. The position has a duration of 3
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Tenure-track Assistant and Associate Professorship positions in Algorithms at the Department of M...
We seek candidates to join the Algorithms Section. The focus of the call is both to expand at the new Vejle campus and to strengthen the Odense campus. We have several openings, and successful
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specialized algorithms supported on solid theoretical foundations and with a focus on challenging aspects of very high-dimensional datasets, such as datasets encountered in the computational biology and
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, theorem provers, type systems, categories, etc.), concurrent programming languages (choreographic programming, session types, etc.), distributed computing (cloud computing, microservices, etc.), Dev(Sec)Ops
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programming, session types, etc.), distributed computing (cloud computing, microservices, etc.), Dev(Sec)Ops, software engineering (software product lines), human factors in security and privacy, post-quantum
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Assistant Professor (tenure-track) and Associate Professor (tenured) Positions in Computer Scienc...
, theorem provers, type systems, categories, etc.), concurrent programming languages (choreographic programming, session types, etc.), distributed computing (cloud computing, microservices, etc.), Dev(Sec)Ops
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, theorem provers, type systems, categories, etc.), concurrent programming languages (choreographic programming, session types, etc.), distributed computing (cloud computing, microservices, etc.), Dev(Sec)Ops
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Assistant Professor (tenure-track) and Associate Professor (tenured) Positions in Computer Scienc...
systems, programming of critical software and infrastructure, high-performance computing, and distributed systems. Model-driven Software Engineering Cybersecurity, including security by design, blockchain
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description You will be contributing to developing and implementing novel algorithms at the intersection of computational physics and machine learning for the data-driven discovery of physical models. You will
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investigate new algorithmic principles that make learning agents adapt to non-stationary environments in an autonomous manner. The expected outcomes are new theoretical insights about the algorithmic roots