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, generative design, building performance optimization, digital design methods (e.g., predictive modeling, multi-agent systems and algorithmic techniques for architectural design), digital design epistemologies
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transformative advancements in scientific discovery. Responsibilities As a Senior postdoc, you will be able to contribute to designing your own project focusing on implementing cutting-edge algorithms for graph
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The Department of Agroecology at Aarhus university has recently acquired state-of-the-art plant phenotyping infrastructure, including a diverse range of UAV sensors for canopy determination, a multispectral camera
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electricity price signals, demand-response mechanisms, and time-of-use optimization. AI-Driven Optimization using Reinforcement Learning: Apply RL algorithms to develop and train agents that optimize power
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background within (at least one, preferably several of) the following fields: Biomedical circuits and systems Physiological Modelling Medical sensor and instrumentation technology Health Informatics Digital
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integrate machine learning algorithms and Earth System Models to emulate carbon processes in the ocean connected to the biological activities. You will be enrolled in DTU’s Section for Oceans and Arctic and
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separate job advert “Postdoc in advanced reconstruction algorithms for time-resolved nano CT of sustainable cement ”) Research and teaching efforts at a section and departmental level as appropriate and
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on developing machine learning algorithms to support the use of complex urban simulators in decision-making under uncertainty. This PhD project shifts the focus from optimality to relevance in urban land-use and
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portfolio projects with SMEs, where new technologies, such as electronics, sensors, and digital technologies are implemented in new products and processes concerning integration of user needs, sustainability
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involves the use of quantum chemistry, machine learning, and genetic algorithms to search for new homogeneous chemical catalysts. Who are we looking for? We are looking for candidates within the field