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SFI FAST: PhD position in Microstructure/texture evolution during extrusion of scrap-based Aluminium
fellowship starting in 2026. The PhD candidate will be embedded in the research activities of SFI FAST centre related to forming processes and will work closely with NTNU, SINTEF, and leading international
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into an action–perception loop that drives the optical tweezers Use and further develop simulation tools to design and benchmark control strategies before deploying them on the microscope Integrate your software
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://www.academictransfer.com/en/jobs/359398/phd-position-in-high-performanc… Requirements Additional Information Website for additional job details https://www.academictransfer.com/359398/ Work Location(s) Number of offers
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… Where to apply Website https://www.academictransfer.com/en/jobs/359399/phd-position-in-high-performanc… Requirements Additional Information Website for additional job details https
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of personal data as part of the application and selection process, please refer to the privacy policy on our website at https://www.senckenberg.de/en/imprint/ Please visit our website at www.senckenberg.de
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application! We are looking for a PhD student for sustainable and resource-efficient machine learning. Your work assignments Machine learning has recently advanced through scaling model sizes, training budgets
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are in compliance with the necessary trainings (both at the lab and at the institutional level). Minimum Education and Experience: A PhD degree in Computer Science, Electrical/Computer Engineering, or a
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-impact weather A dedicated computer scientist/software engineer works alongside you to set up ICON-CLM on the HPC systems, support simulations and manage large data volumes—so you can focus on the science
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and governance processes. 2. Liaise with data controllers and research coordinators to identify the content of specific administrative datasets and verify their use for addressing specific research
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big-picture questions. Preferred Qualifications: Experience with computational topology software (e.g., GUDHI, Ripser, giotto-tda, or similar). Familiarity with natural language processing (NLP