58 computer-science-image-processing-"the"-"Washington-University-in-St" PhD positions in Germany
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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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the Phytophotonics department, you will work as part of an interdisciplinary team at the interface between plant sciences and optical technologies. The focus is on various spectroscopic and imaging methods
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Your Job: We are offering a PhD position dedicated to the advancement of cryo-EM image analysis methods at the interface of Structural Biology and Electron Imaging at the Forschungszentrum Jülich
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. Given this, the CUI: Advanced Imaging of Matter Graduate School features an interdisciplinary research and training programme for doctoral students and post-doctoral researchers. It is addressed to young
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with reducing and oxidising gas-phase species (e.g. laser-based imaging diagnostics, setup of model reactors, modelling of underlying reactions, multi-scale simulation of reactive fluids, computational
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and the willingness to work in a team are expected. Our offer Work in a dynamic, international and interdisciplinary environment Close cooperation with computer scientists of the Research Group Data
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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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Max Planck Institute for Multidisciplinary Sciences, Göttingen | Gottingen, Niedersachsen | Germany | 2 months ago
of critical thinking Experience with photonics, fluorescence, imaging or biochemical methods is helpful Our offer Highly motivated team Flexible working hours World-class institute with outstanding
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, memristive devices), and the evaluation with e.g. machine learning and image processing benchmarks Requirements: excellent university degree (master or comparable) in computer engineering or electrical
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imaging techniques developing computational codes to process and understand large experimental datasets (e. g., image processing) analyzing experimental results; developing conceptual models and