16 algorithm-development-"LIST"-"Washington-University-in-St" PhD positions in Netherlands
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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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limitations. The field of interpretable machine learning aims to fill this gap by developing interpretable models and algorithms for learning from data. Meanwhile, the field of knowledge discovery and data
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, the researcher will develop theory and algorithms for (hybrid) model selection that allows to exploit domain knowledge through interactive learning. For this we will build on the minimum description length (MDL
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, the researcher will develop theory and algorithms for (hybrid) model selection that allows to exploit domain knowledge through interactive learning. For this we will build on the minimum description length (MDL
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-learning energy trading algorithms that are able to cope with these challenges. By leveraging real-time data, developed algorithms continuously adapt to market dynamics and respond to changing market signals
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Description We are looking for a PhD-candidate interested in topics that lie on the border of optimization by the use of heuristic algorithms and (Explainable) Artificial Intelligence ((X)AI). Specifically, in
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new generation of perceptual foundation models by contributing advanced perceptual pre-training and fine-tuning algorithms. What you will do You will carry out research and development in the areas
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-tuning algorithms. What you will do You will carry out research and development in the areas of perceptual foundation models, using advances in deep machine learning and computer vision. The goal is to
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Vacancies PhD position on Stochastic geometric numerical methods Key takeaways Are you passionate about developing cutting-edge numerical algorithms at the intersection of geometry, stochastic
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on the theoretical and algorithmic development of control methods that combine physical modeling and real-time computation. The work will involve deriving reduced-order models, designing controllers that exploit