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into goal-directed behavior. We use state-of-the-art approaches including functional brain imaging, automated behavioral analysis, and computational neuroanatomy. We value a collaborative atmosphere, early
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Assistant (Doctoral Candidate) with specialising in multimodal imaging (salary scale 13 TV-L, 65 %) The fixed-term position is for a duration of 36 month in accordance with the project duration. Your role In
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to understand, predict, and treat diseases. You will work with multimodal biomedical datasets including omics, imaging, and patient data and apply cutting-edge AI models such as graph neural networks, transformer
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microscopy and automated image analysis Basic knowledge of toxicology (e.g. through DGPT training courses or relevant studies / professional experience) Experience in establishing test methods Conscientious
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hydrological community. Alternatively, it is well known that Neural ODEs [2] are capable of representing dynamic systems that are coded in ODEs. They can encapsulate the complex temporal dependencies and
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characterization, clean-room processes or magnetic imaging Past experience in Micromagnetic or Atomistic simulations is desirable, but not mandatory Willingness to work closely with collaboration partners and travel
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(CPS). We built on prior work on MLIR to create a code generation framework that optimises not only for performance and energy efficiency, but also for reliability and security concerns identified in
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and IT develop innovative radiopharmaceuticals and novel tools for functional characterization, improved imaging and personalized treatment of tumors. The Department of Department Life Science
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partner interactions in a laboratory context, including video-based behavior coding. Your responsibilities Developing an independent research question in the Emmy Noether Project AMOR on personality
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equally qualified, those with disabilities or with equivalent status pursuant to the German Social Code IX (SGB IX) will receive priority for employment. Please submit your detailed application including a