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, electrical engineering, machine learning, data science, computer science, applied mathematics or in a similar field, or have completed at least 240 credits in higher education with at least 60 credits at
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physics, electrical engineering, image processing, computer vision, AI, machine learning, data science, computer science, applied mathematics, or in a similar field, or have completed at least 240 credits
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expertise from control theory, machine learning, optimization, and network science, spanning diverse application domains such as energy systems, biomedical systems, neuroscience, and safety and security
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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 the support of
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of ion conductivity in complex battery materials on a large scale. Model‑generated data will be used to identify key relationships between material structure and ionic conductivity through advanced data
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technology Researcher Profile First Stage Researcher (R1) Application Deadline 14 May 2026 - 21:59 (UTC) Country Sweden Type of Contract Temporary Job Status Full-time Is the job funded through the EU Research
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Learning and Control Laboratory , an interdisciplinary research group doing basic and applied research at the intersection of cybersecurity, control theory, and machine learning. Our vision is to develop
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changes of photoreceptor proteins using time-resolved diffraction methods. A concrete goal will be to structurally characterize the structural effects of charge transfer (for example in cryptochrome and