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Optimization and Machine Learning for Hydrogen Technologies The Natural Computing Group (NACO) at LIACS, Leiden University, is seeking a highly motivated researcher to join our cutting-edge project on AI tool
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) are looking for a: PhD Candidate on Multi-Objective Optimization and Machine Learning for Hydrogen Technologies The Natural Computing Group (NACO) at LIACS, Leiden University, is seeking a highly motivated
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. Your work will focus on design-space exploration and optimizations tailored to different environments. The optimizations range from algebraic optimizations (e.g., term rewriting), to algorithmic
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, and stochastic optimization, embracing an interdisciplinary approach. The candidate will be embedded in the Explanatory Data Analysis group at the Leiden Institute of Advanced Computer Science. More
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understood. Especially for soluble ligands that are not expressed on cells, it is unknown what receptor: ligand dynamics lead to optimal receptor activation. In this project, funded by the ZonMW Open
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underlying the discovery and optimization of drugs, and personalised medicines. We aim to optimise the route to novel drugs that are both efficacious and safe, and therefore our research focuses on drug
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therapies. Project description Antimicrobial combinations are essential for combating antimicrobial resistance (AMR) and treating complex infections. However, selecting the right combinations and optimizing