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(e.g. fuel cells, batteries, heterogeneous catalysts, interfaces) Proficiency in high-level programming languages, e.g. Python Previous supervision of graduate students, as well as laboratory
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interfaces (application programming interface, API) for system control are being developed in order to automate both process monitoring and process control. The API-based integration of the digital twin
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, Statistical Physics, Genome Annotation, and/or related fields Practical experience with High Performance Computing Systems as well as parallel/distributed programming Very good command of written and spoken
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research studies for automated image analysis. In particular, you will: Plan, develop, and implement AI/ML algorithms for pathology image analysis. Integrate multi-modal data (e.g., genomics, clinical data
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for livestock systems in East Africa, and in the subtropics in Latin-America. The research programme will examine productivity of grasslands, nutrient stocks and cycling and their relationship to biodiversity. We
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the subtropics in Latin-America. The research programme will examine productivity of grasslands, nutrient stocks and cycling and their relationship to biodiversity. We conduct experiments in the field
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available in the further tabs (e.g. “Application requirements”). Programme Description As part of the HessenFonds, the Hessian Ministry of Higher Education, Research, Science and the Arts provides
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machine and deep learning Programming experience with Python and Pytorch Strong analytical and problem-solving skills Excellent communication & interdisciplinary skills Fluency in English (written and
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Institute (https://www.mdsi.tum.de/). The Position Plan, develop and test novel computational models for the analysis of digital pathology image data. Collaborate with pathologists and other domain experts
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of linear algebra and numerical optimization Understanding of statistical modeling and inverse problems is desirable Experience with programming languages like Python, MATLAB, or C++ Joy in dealing with