9 condition-monitoring-machine-learning Postdoctoral positions at UNIVERSITY OF HELSINKI
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The Faculty of Science invites applications for a POSTDOCTORAL RESEARCHER IN MACHINE LEARNING FOR NATURE CONSERVATION starting from August 2025 or as agreed. The Postdoctoral Researcher will be
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. We require the candidate to have documented experience in either large-scale genomics data analysis with computational or approaches/biostatistics, or machine learning/deep learning. Experience with
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of large-scale genomic data sets is a requirement for this position. Experience with data integration, machine learning, network science, cancer biology, and/or gene regulation is considered an advantage
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multiscale solute transport in nanoporous media under changing conditions. The post-doctoral position is for a period of 28 months. Background of the project Quantification and prediction of solute movement
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dysfunction. An ensemble of multi-scale computational approaches (molecular dynamics simulations, quantum chemistry, machine learning) are applied to study the mechanistic aspects of biomolecules in great depth
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applications in different industries, including health technologies. A particular application area is wearable devices for continuous glucose monitoring. Our technology aims to improve the durability and
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sustainable policies for human flourishing. This includes identifying social and environmental inequalities, supporting inclusive social action and policies, informing learning and education, promoting
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reinforcing its status as a distinguished institution of multidisciplinary education in healthcare: https://www.helsinki.fi/en/faculty-of-medicine The Faculty of Medicine at the University of Helsinki
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of the best medical research faculties in the world, while reinforcing its status as a distinguished institution of multidisciplinary education in healthcare: https://www.helsinki.fi/en/faculty-of-medicine