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associated with the Wallenberg (DDLS-WASP) project Machine-Learning how our Cells Capture Energy - Data-Driven Studies of Membrane Protein Function, Evolution, and Disease. We are searching for a highly
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: www.scilifelab.se/data-driven . Project description The position will be associated with the Wallenberg (DDLS-WASP) project Machine-Learning how our Cells Capture Energy - Data-Driven Studies of Membrane Protein
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group of Assoc. Prof. Kruve and associated with the ERC project ” Machine Learning and Mass Spectrometry for Structural Elucidation of Novel Toxic Chemicals”. The project aims to develop novel machine
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AI and mass spectrometry is essential. Candidates with experience with machine learning are encouraged to apply, while experiences in generative models and high resolution mass spectrometry
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problem-solving mindset. The ambition to conduct research on the interface generative AI and chemictry is essential. Candidates with experience with machine learning are encouraged to apply, while
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background in computational hydrological and/or hydro-climate research with a focus on extreme events Programming, hydrological modeling, remote sensing, machine learning and spatial data analysis skills A
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machine learning within fundamental physics, astrophysics, particle physics or cosmology. Main responsibilities Research and in addition some teaching and supervision. Qualification requirements In order to
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approximately 70 employees, including around 10 technical administrative staff and about 15 PhD students. Its activities span three areas: geology, geochemistry, and marine geoscience, encompassing both research