465 engineering-computation "https:" "https:" "https:" "https:" "https:" "https:" positions in Germany
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- Leibniz-Institute for Food Systems Biology at the Technical University of Munich
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- Max Planck Institute of Immunobiology and Epigenetics, Freiburg
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- Technical University of Munich •
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Master`s program in the field of process engineering, chemical engineering, energy engineering, environmental engineering, or a related field Good knowledge of thermodynamics, process engineering, and
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)computer science, (bio)physics, mathematics, engineering or similar degree from STEM - advanced programming skills in Python - experience with ODE modeling, in pharmacokinetics, ADME, pharmacology
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publications and project reports Support in establishing the institute Your Profile: Master`s degree in physics, chemistry, materials science, chemical engineering, or a related discipline Extensive knowledge
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Carl von Ossietzky University of Oldenburg • | Oldenburg Oldenburg, Niedersachsen | Germany | 2 days ago
neurosensory science, hearing research, communication technology and auditory rehabilitation within the Cluster of Excellence "Hearing4all". We provide a structured, three-year doctoral programme focusing
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electrical engineering, computational engineering, or a related discipline A strong foundation in power system modelling and simulation Solid programming skills (Python, C++, or comparable languages) Interest
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PostDoc/Senior Scientist - Process and Plant Design in the Field of Liquid Organic Hydrogen Carriers
reactor design and efficient heat integration Collaboration with the department experimental technology testing for the implementation of processes at laboratory, miniplant, pilot, and demonstration scale
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Description TUD Dresden University of Technology, as a University of Excellence, is one of the leading and most dynamic research institutions in the country. Founded in 1828, today it is a globally
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, train and test novel machine-learning-based solutions on top-tier super-computing hardware Work in an interdisciplinary team of engineers, computer scientists, and life scientists Regularly participate in
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science, engineering, physics, biophysics, applied mathematics, computational biology or a related quantitative field Strong background in deep learning for image analysis / computer vision, ideally on microscopy time
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entropy or Kullback-Leibler divergence vs. measurement time Analysis and documentation of the results Your Profile: Excellent academic performance in a master’s program in electrical engineering, materials