74 phd-studenship-in-computer-vision-and-machine-learning Postdoctoral positions at Technical University of Denmark
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experience in developing software for processing SURE and ULM data Have a desire to advance the field and help PhD students learn We offer DTU is a leading technical university globally recognized
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systems Strong skills in data-driven analysis and modelling, simulation, control, and validation Familiar with modeling of PtX and storage technologies, model predictive control, machine learning
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, you will contribute to research-based teaching and the supervision of student projects. Skills in mathematical modelling and machine learning of relevant physical glacier processes (ice sheet and
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Job Description These days, the inner workings of molecules and materials can be probed and modelled by advanced simulation tools on modern computer architectures. However, the routine applications
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of public-health professionals and PhD-students. The day-to-day work will be performed in close collaboration with other researchers in the Risk-benefit Research Group and within the project consortium
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. Research-based teaching in GNSS, geodesy, and surveying. The teaching must be conducted in Danish and English at bachelor’s (BSc) and master’s level (MSc) Co-supervision of BSc, MSc, and PhD projects Public
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include: Skills in mathematical modelling and machine learning of relevant physical glacier processes (ice sheet and mountain glaciers), with proficiency in MATLAB/Python/Fortran, and related software tools
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experimental techniques. As a formal qualification, you must hold a PhD degree (or equivalent). You must have: Documented expertise in either computational protein design or wet lab techniques, with a
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or related fields. Preferably strong interest and foundation in immunology, immune cell assays, or translational research. Preferably experience with computer-guided protein engineering. Experience in human
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of structural response models against measurements. Support the structural dynamics and multi-body modelling efforts in HAWC2. Teach and supervise BSc and MSc student projects and be co-supervisor for PhD