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include: Skills in mathematical modelling and machine learning of relevant physical glacier processes (ice sheet and mountain glaciers), with proficiency in MATLAB/Python/Fortran, and related software tools
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of the areas listed on the page above are of interest to you. The list includes positions covering Operator Algebras, Machine Learning, Analytic Number Theory, Automorphic Forms and Representation Theory
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history analysis and possibly also with machine learning. Another specific example is statistical software development, e.g. implementing tools and algorithms for working with causal discovery
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, you will be asked to indicate, which of the areas listed on the page above are of interest to you. The list includes positions covering Operator Algebras, Machine Learning, Analytic Number Theory
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systems Strong skills in data-driven analysis and modelling, simulation, control, and validation Familiar with modeling of PtX and storage technologies, model predictive control, machine learning
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(e.g., based on physiological signals or direct inputs from occupants) and developing algorithms, including machine learning methods. The work will include statistical modelling, data-driven modelling
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Post Doctoral Researcher in Digital Twins CO2-to-Protein production in collaboration between the ...
collaboration between the Department of Electrical and Computer Engineering and the Novo Nordisk Foundation CO2 research center, Aarhus University, we aim to address this opportunity by developing digital twins
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Sustainability in association with Professor Christina Lioma and her Machine Learning research team in the Department of Computer Science at the University of Copenhagen. The sub-package focuses
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, Denmark, invites you to apply for a 7-month Research Assistant position funded by the IFD project “Cyber-physical systems for machines and structures – CP-SENS”. Expected start date and duration of
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, including use of scientific libraries (e.g., NumPy, Pandas, Matplotlib, etc). Experience with machine learning (e.g., Scikit-learn, PyTorch) or physics-informed neural networks for thermal systems is a plus