75 post-doc-in-machine-learning Postdoctoral research jobs at Technical University of Denmark in Denmark
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digital technologies within mathematics, data science, computer science, and computer engineering, including artificial intelligence (AI), machine learning, internet of things (IoT), chip design
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Job Description The advertised position is within an ongoing post doc project related to the research project HyProFuel, funded by Innovation Fund Denmark. The project deals with the development
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is looking for a post doc with a background in seafood science and/or seafood development or processing for a large project in collaboration with Food and Agriculture Organisation (FAO), which is an
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simulations using, e.g., COMSOL, Lumerical, or other Maxwell solvers. Experience with machine learning algorithms is an advantage but not required. General qualifications Scientific production and research
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Job Description The Section of Bioinformatics, DTU Health Tech is world leading within Immunoinformatics and Machine-Learning. Currently, we, together with Lonza Cambridge, UK, are seeking a highly
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Embedded AI, Edge AI, TinyML, and AIoT, that can be documented by a publication record in relevant venues. Solid understanding of state-of-the-art embedded machine learning techniques. Experience in system
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the lab? Join a collaborative post project at DTU Bioengineering focused on the de novo design of Carbohydrate-Active enZymes (CAZymes). About the position The postdoc project is part of a 4-year project at
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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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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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collaboration with the interdisciplinary team at DTU Construct, DTU 3D Imaging Centre, and DTU Compute. Research and teaching efforts at a section and departmental level as appropriate and relevant (e.g., teach