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solvers and optimization algorithms for 1 year and 4 months. The Section of Solid Mechanics conducts research and teaching in the fields of structural and materials mechanics, vibration and their active
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statistical and machine learning techniques for dynamic energy system modelling Develop advanced optimization algorithms for building energy management and control (e.g., MPC, RL) Develop and evaluate digital
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an optimal molecular representation (including data procurement) and integrating generative model and binding oracles. Propose an algorithm to bias the generative models towards desirable properties, such as
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for human control of complex robotic systems with high levels of agency and minimal cognitive effort. Short description: This project will develop novel AI algorithms to decode human intention from
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of solvers for stochastic optimization problems, and test the methods on real-life data. As part of the PhD you will be following advanced courses to extend your skills, implement and test algorithms, and
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(entities) given the rules and the rules given the molecules. The aim of this project is to develop a theory and accompanying algorithms to decide if an abstract system can be instantiated by a concrete
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the loop and using active learning to determine which demonstrations to collect. The candidate would work on both projects and be responsible for: Implementing AI and probabilistic ML algorithms Development
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algorithm development in the biomedical context. We are particularly, but not exclusively, interested in candidates with competence in multi-modal data integration, including electronic health records, omics
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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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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