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for materials discovery. Project description Machine learning opens up new opportunities to accelerate the discovery of next-generation energy materials by combining predictive and generative approaches. In
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, you will contribute to research-based teaching and the supervision of student projects. Skills in mathematical modelling and machine learning of relevant physical glacier processes (ice sheet and
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Post Doctoral Researcher in Human-centred Large Language Models for Software Engineering, Departm...
to Software Engineering for some time, and in areas such as software effort estimation, defect prediction, and project management in general. And more recently, the proposal of Large Language Models opened a
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. Responsibilities: Conduct research in compilation, optimization, and analysis for time-predictable computer architecture. Co-supervise MSc and PhD students. Contribute to teaching and research proposal preparation
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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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thermal and/or thermochemical energy storage systems. Implementing and validating advanced thermodynamic models for performance prediction and optimization. Collaborating with experimentalists and industry
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/or high-temperature heat pumps based on power cycles. Design thermal and/or thermochemical energy storage systems. Implementing and validating advanced thermodynamic models for performance prediction
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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