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Job Description Are you interested in working at the intersection of optimal control, AI algorithms, and game theory, on problems that matter for real-world critical infrastructure? This PhD
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) for measuring the quality, shape and the neutron focusing performance of the Wolter optics. The work will be performed in close collaboration with a postdoc who will work on simulating the optimal design of
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projects; this can entail working alongside domain experts to extract relevant knowledge, and programming using suitable models to infuse that knowledge with ML methods, thus aiming to optimize performance
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engineering, acoustics, machine learning or similar; Solid mathematical and analytical skills, including signal processing, optimization, machine learning or information theory; Experience in programming, e.g
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, mathematical engineering, acoustics, machine learning or similar; Solid mathematical and analytical skills, including signal processing, optimization, machine learning or information theory; Experience in
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Engineering. Food approved microorganisms will be optimized using classical mutagenesis/screening and adaptive evolution. Genetic engineering will be used for guidance and to elucidate the effect of introduced
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. The position is offered in relation to the research program "Power Electronic Control Reliability and System Optimization" and the PhD Student will be positioned to the section for “Applied Power
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"Power Electronic Control Reliability and System Optimization" and the PhD Student will be positioned to the section for “Applied Power Electronic Systems”. How to apply Your application must include
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full ownership of their own research project. Responsibilities Design and execute LC-MS/MS-based proteomics experiments (primarily in negative ion mode) Independently operate and optimize chromatographic
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. Computational modeling and data-driven analysis will be used to guide material selection, molecular design, and performance optimization. Experimental input will be limited and used selectively for validation