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intelligence, and high-performance computing to study metabolic networks and optimize microbes for biotechnological applications. The PhD project aims to predict the optimal compartmentalization of a production
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candidates with expertise in Operations Research, Management Science and Business Analytics with a focus on fundamental research in combinatorial and stochastic optimization for business applications. In
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data, stochastic optimization, modern machine learning methods, scalable algorithms for advanced Machine Learning techniques and explainable AI. In teaching, the position will contribute, inter alia
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routine maintenance, troubleshooting, and setup of instruments within the Mass Spectrometry unit of the Research Support Facility. • Supporting data analysis for collaborators and optimizing sample
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participate in interventional human studies investigating the effects of specific collagen peptides on cognitive functions, functional joint health, osteoporosis, and their optimal dosage. You will work at the
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excellent organizational skills Passion for developing and optimizing advanced data infrastructures Experience handling sensitive data and familiarity with relevant data protection standards (e.g. GDPR
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interest in using computational methods such as cognitive and psychophysiological modeling, (Bayesian) statistics and optimal experimental design, and agent-based modeling to address problems in
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spectrometers with a focus on GC-HRMS and Orbitrap analysers Develop, optimize, and validate analytical GC-MS and LC-MS methods for various applications Provide training, consultation and technical support to
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prae doc, you will work on the development of a novel method for the identification of active small organic molecules. The project investigates the use of machine learning and/or optimization methods
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materials that deliver optimal light absorption, catalytic activity, and energy transport. Molecular simulation methods and quantum theoretical calculations in principle can address this but have hitherto