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questions. The candidate should be organized, curious, analytically rigorous and comfortable learning unfamiliar methods. Good written and spoken English is essential. Research motivation: a clear interest in
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Heidelberg Institute for Theoretical Studies (HITS gGmbH) | Heidelberg, Baden W rttemberg | Germany | about 15 hours ago
) in Geometric Deep Learning to join the Machine Learning and Artificial Intelligence (MLI) g roup to perform research in geometric deep learning for materials science. This research is part of
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interaction, geo-information science, or a related field, with experience in experimental research using virtual reality? If so, we have an exciting PhD opportunity for you! Spatial thinking plays a crucial
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ReDiLEEP training in response diversity methods, data management, reproducible code, R/Tidyverse, machine learning and AI for ecologists, visualisation, evidence-based policymaking, science-policy
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FieldComputer scienceEducation LevelMaster Degree or equivalent Skills/Qualifications Strong foundations in Machine Learning and Deep Learning Excellent Python programming skills Experience with PyTorch
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childhood through adolescence. Data collection will primarily take place in schools, where children and adolescent research participants will complete computer-based learning tasks designed to capture
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important that you are able to: A good team player A good communicator Eager to learn Results-oriented Work independently Emphasis will be placed on personal qualities. We offer An exciting job with an
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stays at foreign educational institutions Support to education activities in courses within the Software Engineering area Other career-promoting work, such as learning grant preparation fundamentals Be
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stays at foreign educational institutions Support to education activities in courses within the Software Engineering area Other career-promoting work, such as learning grant preparation fundamentals Be
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Campus (LLEC). Development of physics-informed and graph-based machine learning methods for energy system monitoring, forecasting, and planning Data analysis considering uncertainties, missing data