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preferably start around 01-12-2025 and requires knowledge of geometric image processing and machine learning. Information As Post-doctoral Researcher within VICI Project "Geometric Learning for Image Analysis
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Helmholtz-Zentrum Dresden-Rossendorf - HZDR - Helmholtz Association | Dresden, Sachsen | Germany | 23 days ago
PhD in the field of Medical Physics or comparable applied/natural science # Profound knowledge in machine-learning and strong affinity to apply this in the field of radiotherapy # Expertise in
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contributed to the identification of vaccine and therapeutic candidates currently being produced in Good Manufacturing Practice facilities for early phase clinical trials. Minimum Requirements: PhD in
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Researcher in FPGA-based AI Hardware Acceleration who has: strong experience in FPGA design, machine learning or a related field in the case of the Postdoctoral Research Associate, a PhD (or near completion
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foundations of feature learning in neural networks. Engage in the life of the CSD, including participating at the weekly seminars. Present results internally and at international venues; Qualifications PhD in
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: High Energy Physics / accelerator , astrophysics , BSM , CMS , cosmology , Dark Matter , Experiment , Flavor Physics , Higgs physics , Lattice QCD , LHC , Machine Learning , Neutrino , Neutrino physics
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Acceleration who has: strong experience in FPGA design, machine learning or a related field in the case of the Postdoctoral Research Associate, a PhD (or near completion) in FPGA design, machine learning or a
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, including development of new computational tools for processing large-scale biospecimen data Creation of novel machine learning frameworks for automated scientific analysis and discovery Design and
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analysis, multi-omics analysis, differential analysis, machine learning methods. Definition of tasks to be performed: Fixed-term contract essential to carry out the bioinformatics part of the project
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employ cutting-edge single-cell and spatial omics technologies with bioinformatics and machine learning to decipher principles of gene regulation underlying cell identity and its disruption in human