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/or spatial genomics, computational biology, machine learning, bioinformatics, and systems neuroscience. Prior experience with deep learning applied to biological data is a plus. Practical experience
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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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of energy. Approximately 25 colleagues work in the division, including 15 PhD students. On the international level we collaborate with universities and institutes in Europe, Asia, and North America
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9 Jan 2026 Job Information Organisation/Company Lunds universitet Department Lunds universitet Research Field Chemistry Researcher Profile Recognised Researcher (R2) Country Sweden Application
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Institute of Molecular Mechanisms and Machines, (IMOL), Poland, and the Leicester Institute of Structural and Chemical Biology, United Kingdom. Your work may include clinical and biomedical projects. It may
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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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description and working tasks The project will develop privacy-aware machine learning (ML) models. We focus on data-driven models for complex and temporal data, including those built from synthetic sources
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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