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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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, 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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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. 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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Optimization" and the PhD Student will be positioned to the section for “Applied Power Electronic Systems”. How to apply Your application must include the following: Application, stating reasons for applying and
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great extent. 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
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evaluate the devices in ex vivo human tissue samples in collaboration with surgeons. Your primary tasks will be to: plan and execute experimental research design, fabricate and optimize flexible
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devices Optimization of waveguides for photon pair sources Design and characterization of sources of entangled quantum states. SiCPIC PhD student Qualifications Candidates must have a two-year master's