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. Variational Autoencoders, Normalized Flows, Generative Adversarial Networks) Have experience in developing fast algorithms for hard combinatorial optimisation problems. Have some knowledge about stochastic
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better and faster decisions when assessing funding applications, ensuring the efficient and unbiased elimination of poor applications? This question can be addressed through training algorithms on past
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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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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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(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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(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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algorithm. Design methods: Develop novel control methods for power electronic converters feeding electric machine Simulation: Learn advanced simulation tools such as Ansys to simulate and analyze the effect
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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
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-transpositions (plastys) and suture practices for surgical procedures. The specific PhD-project aims at developing efficient hyper elastic-based topology optimization algorithms that take into account skin
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Job Description We invite applications for a fully funded PhD position focused on the development of advanced computer vision and machine learning algorithms for detection and identification