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Field
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-quantitative histomorphometry and image analysis In vitro endothelial and co-cultur models High content imaging and spatial biology (cooperation AG Schapiro, Heidelberg) Single molecule localisation microcopy
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benchmarking of clay mineral surface finite models for DFT simulations Speciation simulations of the radionuclides in various environments Your profile Completed university studies (Master/Diploma) in the field
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quantitative image analysis, numerical modeling, and explainable AI (XAI) with state-of-the-art biophysical methods. Using techniques such as traction force microscopy, microfluidics, 3D bioprinting, and
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12.11.2025, Wissenschaftliches Personal Join our team in a collaboration between TUM and Politecnico di Milano! Develop cutting-edge methods combining remote sensing, physics-based modeling, and
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! Overall, research in the Group of Prof. Dr. Meyer zu Hörste at the Department of Neurology combines basic models and patient-derived specimen with cutting-edge technologies. One of our recent projects has
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of different medial temporal lobe areas such as CA1, CA3, DG, MEC, LEC, PrC, POR to memory in health, aging and in animal models of amnesia. Memory for time, space and episodes as well as the consolidation and
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Deutsches Zentrum für Neurodegenerative Erkrankungen | Ulm, Baden W rttemberg | Germany | 17 days ago
sclerosis (ALS) and Parkinson’s disease. Using next-generation sequencing, we have identified Mendelian disease genes that cause autosomal-dominantly inherited ALS. We have developed innovative disease models
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, MATERIALS SCIENCE, MODELING AND SIMULATION, MOLECULAR SIMULATIONS, NUCLEAR WASTE MANAGEMENT, PLASMA PHYSICS, PHOTOVOLTAICS, SYNTHETIC FUELS AND GREEN CHEMICALS, SYSTEMS ANALYSIS, TECHNOLOGIES FOR THE HYDROGEN
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highlight the potential of microbiome intervention in immuno-oncology. In our team, we actively integrate translational data, functional assays and preclinical models, to understand and overcome mechanisms
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, particularly insect decline and species distribution models (SDMs), are desirable • Experience with and knowledge of a programming language commonly used in data science (e.g., R or Python) • Experience and