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position is part of the national research programme DDLS. Data-driven life science (DDLS) uses data, computational methods and artificial intelligence to study biological systems and processes at all levels
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collaboratively Meritorious qualifications: Experience with machine learning or deep learning Experience with computer vision or image analysis Experience with 3D data, geometric representations, or parametric
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to receiving your application! Data-driven life science (DDLS) uses data, computational methods and artificial intelligence to study biological systems and processes at all levels, from molecular structures and
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. Experience with fluorescence-based characterization of lipid mixtures, including via imaging and spectroscopic methods, are a plus. Willingness to perform or analyze additional computational simulations
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KTH Royal Institute of Technology, Scool of Electrical Engineering and Computer Science Job description Cellular morphology reflects fundamental biological processes such as division
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-Driven Life Science (DDLS) uses data, computational methods, and artificial intelligence to study biological systems and processes at all levels, from molecular structures and cellular processes to human
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, incorporating their own ideas and experience in computer vision, machine learning, and related fields, to further visualization and interpretation of molecular images. Our research environment focuses
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School Data-driven life science (DDLS) uses data, computational methods and artificial intelligence to study biological systems and processes at all levels, from molecular structures and cellular processes
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Data-driven life science (DDLS) uses data, computational methods and artificial intelligence to study biological systems and processes at all levels, from molecular structures and cellular processes
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++ or similar) and an interest in quantitative or computational approaches are required. Prior experience with image analysis, machine learning, signal processing, or structural biology is meritorious but not