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, calorimetry, and synchrotron experimental measurement techniques. Knowledge of AI-based and machine-learning methods is also beneficial. For further information about a specific subject see General syllabus
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The continuous release of Earth Observation (satellite) data and the emergence of Machine Learning methods open up new possibilities for understanding forests. These large datasets provide
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of offers available1Company/InstituteDepartment of Computer ScienceCountryAustriaCityInnsbruckPostal CodeA-6020StreetTechnikerstraße 21 a Contact City Innsbruck Street Technikerstraße 21 a Postal Code A-6020
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Constructor Technology, invites applications for a PhD position in machine learning for software engineering and formal methods, on the Constructor Fabric project. Constructor Fabric turns a company's informal
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University of Science and Technology (NTNU) has a vacant position as PhD candidate in the field of machine learning for materials science. Your immediate leader will be the Head of Department. About the
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knowledge for a better world. You will find more information about working at NTNU and the application process here. About the position We have a vacancy for a PhD candidate in machine learning
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mapping technologies. This PhD would particularly suit candidates with backgrounds in: Artificial intelligence or machine learning Computer science Data science or computational modelling Engineering
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English 3-years PhD position in probabilistic machine learning and statistics Apply for this job See advertisement About the position We invite applications for a three-year PhD Research Fellowship in
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architectures for foundation models The work will combine methodological development with large-scale experiments, aiming for contributions at leading machine learning and computer vision venues such as NeurIPS
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27 Sep 2026 Job Information Organisation/Company Delft University of Technology (TU Delft) Research Field Engineering » Materials engineering Researcher Profile First Stage Researcher (R1