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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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given language. This question has practical implications, such as in compiler optimizations and decompilation for tasks like malware analysis. However, theoretical limits exist: languages lacking non
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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