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and free-energy calculations in explicit solvent. The postdoctoral researcher will employ machine-learning-accelerated methods throughout the workflow, contribute to the development of new computational
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of possible methodological components include self-supervised temporal representation learning for large volumes of unlabeled AE/electrochemical time-series data, switching state-space models that describe
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the health and MedTech sectors, and beyond. For more information about the total announced post-doctoral positions within in the AMBER co-fund project please visit https://www.euraxess.se/jobs/392999
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12 Dec 2025 Job Information Organisation/Company Lunds universitet Department Lund University Research Field Biological sciences » Other Chemistry » Other Agricultural sciences » Other Researcher
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: S. Aalto). In the project we use multi-wavelength techniques, including recently developed mm and submm observational methods, to reach into the dark hearts of dusty galaxies. New machine learning