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monitoring of compound uptake into P. aeruginosa to guide the optimization process. The project is part of an interdisciplinary collaboration between research groups across several European countries and
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covalent and non-covalent inhibitors and will implement early monitoring of compound uptake into P. aeruginosa to guide the optimization process. The project is part of an interdisciplinary collaboration
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, ill-posed nonlinear inverse problems Numerical optimization techniques Machine learning Strong programming skills in Matlab and/or Python are required. These should be documented, for example through a
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one of the following areas is required: Numerical methods for large-scale, ill-posed nonlinear inverse problems Numerical optimization techniques Machine learning Strong programming skills in Matlab and
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analysis and modeling, the research will support a framework for strategic renewable energy planning, optimizing wind, wave, and solar integration, especially during peak production seasons. Qualifications
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energy planning, optimizing wind, wave, and solar integration, especially during peak production seasons. Qualifications and personal qualities Applicants must hold a master's degree or equivalent
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optimization for antibiotics and research in general The applicant must be motivated for science in general and this position in particular, responsible, and also have a great work capacity Personal skills
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important for renewable energy production and production variability will be an advantage. Knowledge of machine learning or optimization will be an advantage. Applicants must be able to work independently and
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disorders (e.g., Cushing’s disease, metabolic syndrome, cardiovascular disease, sleep and shift work disorders). Beyond clinical applications, the research may contribute to optimizing athletic performance