67 post-doc-machine-learning "https:" Postdoctoral positions at Nature Careers in Denmark
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Antimicrobial resistance (AMR) is a major threat to global public health, causing millions of deaths each year. We are seeking a postdoctoral researcher to develop machine learning and generative
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A position as post doc in structural biology and biochemistry is available at the Department of Molecular Biology and Genetics, University of Aarhus, Denmark. Expected start date and duration of
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cultural events including music festivals etc. See e.g. the recent recommendation by CNN (https://edition.cnn.com/travel/article/aarhus-denmark-things-to-do/index.html). Aarhus is easily reached through
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4 Post Docs and 8 PhD students, among other students and academic and technical staff. The group is part of The Interdisciplinary Nanoscience Center ( iNANO ) and the Novo Nordisk Foundation CO2
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available in the Nielsen Lab, which focuses on understanding how post-translational modifications (PTMs) such as ADP-ribosylation networks regulate proteome states and cellular function. The position is
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Postdoctoral position in the development of an AI-based phenotyping system for high-throughput sc...
close collaboration with a specific group (DARSA) specialized in developing and applying remote-sensing tools and innovative open-source machine-learning methods. Key responsibilities Develop effective
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University and comprises research within the areas of Plant Molecular Biology, Neurobiology, RNA Biology and Innovation, Protein Science, Cellular Health, Intervention and Nutrition. Please refer to http
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analysis or habitat monitoring Highly valued: Experience applying AI or machine learning methods to remote sensing data Experience with drone-based point cloud collection Experience working with or advising
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-driven machine learning approaches, they will improve our understanding of nutrient flows in agricultural landscapes. The postdoc will contribute to the development of databases representing the current
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includes the following tasks: Develop computer-aided design software for modular construction of switchable RNA nanostructures. Develop databases for RNA modules for automated building of atomistic models