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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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Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Are you interested in working with machine learning for batteries, with
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manufacturing. It is meritorious to have previous experience in data analysis and processing with Python (or similar), preferably including documented experience with machine learning tools. It is meritorious
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Facility (ViSp) is a central infrastructure for this project (https://www.umu.se/en/research/infrastructure/visp/ ). The scholarship (30 000 sek/month) is funded by the Carl Trygger Foundation and the
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infrastructures organized in infrastructure platforms, of which the Vibrational Spectroscopy Core Facility (ViSp) is a central infrastructure for this project (https://www.umu.se/en/research/infrastructure/visp
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/department-of-computing-science/ Project 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
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society in transition is key. We also take pride in delivering education to enable regions to expand quickly and sustainably. In fact, the future is made here. Are you interested in learning more? Read here
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, providing excellent opportunities for the prospective candidates to expand the professional network and acquire useful multidisciplinary skills and qualities. Please see our latest publication in Science
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into mechanosensory corpuscles (Nikolaev et al., Sci Adv 2020; Nikolaev & Ziolkowski et al., Sci Adv 2023; Ziolkowski & Nikolaev et al., Sci Adv 2025). This is just the beginning and there is still much to be learned
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. Documented knowledge and experience in computational metabolomics, computational biostatistics, statistical and machine learning, involving analysis of biological multi-modal and multivariate data, or related