13 learning-memory-behaviour Postdoctoral positions at Chalmers University of Technology
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Semiconductors (UMS), aiming to advance the next generation of transistor and amplifier technologies for 6G wireless communication and defense systems. This position offers the opportunity to conduct research in
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, quantum optics, and thermodynamics. The successful candidate will conduct research in close collaboration with team members, take responsibility in supervising PhD students, and interact with international
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fluids, flow-induced pattern formation in both simple and complex flows (e.g. flow instabilities, product defects), multiscale analysis, and the application of machine learning techniques. About the
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you will do Conduct independent research in collaboration with the research group Customize microfluidic platforms by integrating biological barriers and tissue-mimicking materials into chip designs
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, the work might involve implementing new algorithms in the SCT tool Supremica, which is developed by the Automation group. Main responsibilities Conduct research in collaboration with senior researchers and
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to the development of advanced methods for electrode fabrication, with a particular emphasis on electrophoretic deposition. You will also conduct electrochemical testing under applied magnetic fields to improve
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. This unique position combines advanced finite element modeling, machine learning, and experimental studies, while offering the opportunity to contribute to open-source libraries and collaborate directly with an
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modeling, machine learning, and experimental studies, while offering the opportunity to contribute to open-source libraries and collaborate directly with an innovative startup partner. You will be
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group. Main responsibilities Conduct research in collaboration with senior researchers and PhD students in the Automation group, with the primary goal of qualifying for a future academic career
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knowledge base. Main responsibilities include: Conduct benchmarking and further development of risk assessment models and components. Investigate the reliability of accident data, including cross-validation