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of Engineering and Design. Our teaching and research focus lies on computer-based development of engineering products, particularly on the planning and realization of built facilities using computational modeling
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to study translational aspects of cancer (single-cell sequencing of immune cells, organoid co-cultures, cellular engineering via CRISPR/Cas9 technology, in vivo imaging, advanced animal models of allo-SCT
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able to experience hands-on testing of a high-speed and engine-representative compressor further increases of the efficiency and stability margin. The project is highly innovative, will generate
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journals. Close collaboration with team members and colleagues. Essential qualifications: M.Sc. in Computer Science, Machine Learning, or equivalent with interest in Medical Imaging and Deep Learning. Strong
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System analysis, prognosis and control Transport processes Image Processing High Performance Computing Financial Mathematics Materials characterization and testing What you bring to the table You have
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: M.Sc. in Computer Science, Machine Learning, or equivalent with interest in Medical Imaging and Deep Learning. Strong knowledge in Machine/Deep Learning with experience in discriminative models