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vision, machine learning, deep learning and neural networks, as well as courses in python, GPU programming, mathematical modeling and statistics, or equivalent. We are looking for candidates with: A solid
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Applications are invited for a position in the rapidly expanding data analytics run by Prof Adam Dubis. The main focus of the team is to develop deep learning tools for prediction of disease progression
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networks, as well as courses in python, GPU programming, mathematical modeling and statistics, or equivalent. We are looking for candidates with: A solid academic background with thorough computational and
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courses Any HDR student willing to use mathematical modelling and simulation in engineering and physical problems. Eligibility criteria Strong mathematical background Strong analytic abilities Experience in
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of precision fermentation or cell culture - Affinity towards technical tasks and bioprocess control - Advantageous: Experience in mathematic modeling, programming, CAD, microfluidic or bioreactor systems
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Mohamed Pourkashanian, Prof Lin Ma, Dr Kevin Hughes, Prof Derek Ingham Application Deadline: Applications accepted all year round Details This project will investigate the most efficient modelling
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analysis (TEA) or an affinity towards these research questions. - Basic knowledge in bioprocess design, bioengineering and/or mathematic modeling - Affinity towards research question in life cycle
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, Mathematical modelling, Biology, Environmental Science, Physical Geography, or related fields. • Specific research in agricultural-environmental disciplines, and particularly with respect to livestock
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28.07.2023, Wissenschaftliches Personal Prof. Karen Alim’s group on Biological Physics and Morphogenesis at the TUM Campus Garching uses theoretical and experimental methods to investigate how flow
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unbounded variable and instance sets. In addition, novel approaches such as Physics Informed/Guided Learning allows the learning models to capture the underlying physics/patterns and to generate physically