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trading decisions under high price volatility. This PhD position focuses on designing, developing, and evaluating self-learning energy trading algorithms that are able to cope with these challenges. By
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deep learning algorithms. We welcome applications from individuals with experience in: Experience developing deep learning models for real-time image/video segmentation, object tracking, reinforcement
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within a cross-functional team, including software developers, electrical and mechanical engineers. Experience and strong understanding of machine learning algorithms, mathematical modelling, and
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require efficient numerical algorithms to be practical and to enable robust optimization. Therefore, in this project you will: Develop efficient numerical methods and strategies to solve the electromagnetic
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and vice versa. Food system models represent the different activities within food systems (such as production, processing, distribution, and consumption) and incorporate multiple drivers and feedback
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health, air quality and noise pollution. In the project Green and safe routing, the challenge is to develop, validate and test a method that offers personalized, tailored travel and route advice in order
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. students, working on all aspects of RF integration problems You will have ample interaction with multiple industries that are keen to apply your insights You are surrounded by the best (industrial
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, aiming to transform the care for patients with abdominal aortic aneurysms (AAA). You will develop and validate cutting-edge multimodal deep learning models that integrate imaging and clinical data
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of Imaging & AI (MIA) chair, you will join the ZonMW-funded AI for EVAR project, aiming to transform the care for patients with abdominal aortic aneurysms (AAA). You will develop and validate cutting-edge
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circular way can affect each other. While national strategies and missions give directions to address such grand societal challenges, local decisionmakers, such as municipalities and project developers, need