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experience in the following fields. Cyber-physical modelling and simulation Digital Twins Autonomous Agents and Multi-Agent Systems Machine Learning and MLOps Probability & Statistics incl. Python/R Place of
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data analysis and statistical tools Who we are The Department of Ecoscience is engaged in research programs and advisory work covering the major biological subdisciplines. We conduct world-class research
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is to create and combine knowledge on relevant atmospheric flow statistics with AWE time-domain analysis and uncertainty quantification, to determine loads statistics and failure probabilities
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model checking. You should be well versed in basic statistics and practical programming skills is a must. Knowledge about the inner workings of GenAI would be nice but not necessary. You must have a two
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., linear algebra, statistics, optimization, and calculus) is expected, along with programming experience using deep learning frameworks in Python (e.g., PyTorch). While prior knowledge of machine learning
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data analysis and statistical tools Who we are The Department of Ecoscience is engaged in research programs and advisory work covering the major biological subdisciplines. We conduct world-class research
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Mc-Kinney Moller Institute. AID collaborates with leading universities and industry partners across Denmark, Europe, and the United States, driving innovation in artificial intelligence, statistical
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Job Description The Department of Technology, Management and Economics at DTU invites applications for a PhD student position on the topic of using AI to reduce stochastic problems. You will be responsible for developing new methods for decision support in stochastic optimization, using AI and...
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sections spanning the scientific disciplines of mathematics, statistics, computer science, and engineering. We offer education ranging from bachelor's degrees to PhDs and support continuing education, all
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DTU Tenure Track Researcher in Nutrition, Sustainability and Health Promotion with a focus on Sus...
xperience with quantitative research methods, Experience in reproducible statistical analyses (preferably R and Python) and in the peer-reviewed publication of results. Must be able to work interdisciplinary