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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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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
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mathematics Appl Deadline: (posted 2025/12/11, listed until 2026/01/16) Position Description: Apply Position Description Postdoc in Algebra-Geometric Foundations of Deep Learning or Computer Vision KTH Royal
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also try going to the Startpage Technical details Code: 500 About http error codes Server: UMU-WEBSRV05 IP: 172.18.132.5 Time: 2025-11-14 06:08:30
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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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/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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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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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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, 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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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