80 machine-learning-"https:" "https:" "https:" "https:" "https:" Postdoctoral positions in Sweden
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Machines, (IMOL), Poland, and the Leicester Institute of Structural and Chemical Biology, United Kingdom. Your work may include clinical and biomedical projects. It may also include technique development
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located at SciLifeLab in Stockholm. Our research is focused on cell biology, spatial proteiomics and machine learning for bioimage analysis. The aim is to understand how human proteins are distributed in
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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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materials and technologies. Using advanced computational modeling and machine learning, we seek to elucidate the mechanisms governing the self-assembly of lignin in different solvents and the formation
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at the Department of Medical Biochemistry and Biophysics, which offers an international, collaborative, and open-minded research environment. Please visit the lab’s webpage for more information: https://www.umu.se/en
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systems. Combination of behavior with large-scale neural recordings using silicon probes, miniscope, or 2P imaging. Ability to explore and analyze large datasets using modern machine learning methods and a
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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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disease through advanced imaging and biophysical approaches. The research group hosting this position studies Contractile Injection Systems (CIS) — natural protein machines used by bacteria to deliver
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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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/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