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mission products during the exploitation phase, and phase F, including product and processing scenario definition, algorithm definition and evolution for Level 1 and Level 2 products, the calibration and
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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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-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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the development and service contracts for the required software components, including the definition and maintenance of the required processing algorithms, during initial development and later evolutions
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models, analysing structural properties, and developing innovative algorithms with both theoretical rigor and practical relevance. Where to apply Website https://www.academictransfer.com/en/jobs/354359
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the power of cutting-edge digital technologies to implement and manage FAIR (Findability, Accessibility, Interoperability and Reusability) environments for data management and algorithm preservation and
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of EU digital and data regulation? And lead the organisation of an academic workshop and become the co-editor of a special journal issue on artificial secrecy and algorithmic transparency? How does EU law
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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
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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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nature. The PhD candidate will focus on the theoretical and algorithmic development of control methods that combine physical modeling and real-time computation. The work will involve deriving reduced-order