87 machine-learning-"https:" "https:" "https:" "https:" "https:" research jobs in Sweden
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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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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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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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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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/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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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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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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. Documented knowledge and experience in computational metabolomics, computational biostatistics, statistical and machine learning, involving analysis of biological multi-modal and multivariate data, or related
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will (micro-)benchmark Java-based applications using JMH. You will collect performance measurements from real projects, statistically analyse them, and conduct experiments with modern machine learning