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create ground-breaking mathematical tools for data-driven modelling and control of complex processes, which will be efficient in practice and have rigorous theoretical foundations. It is envisioned
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energy system model workflows Your Profile: Master’s degree in computer science, data science, natural sciences, economics, engineering, mathematics or a related field of study Huge interest in data
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, without the use of simulation software familiar to process engineers. In this thesis, we aim to: - Propose generative models for other types of cycles, based on existing models. To do this, we could use
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Aalto University is where science and art meet technology and business. We shape a sustainable future by making research breakthroughs in and across our disciplines, sparking the game changers
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models, and reinforcement learning (RL), which is data-driven, are two powerful control techniques. MPC techniques are well-established, while RL techniques are gaining popularity due to increasingly
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collaborative labs develop and deploy the latest technology, including sensing, data analytics, modelling, simulation, artificial intelligence, and machine learning, and function as dynamic hubs where innovative
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Job Description We invite applications for a 3-year PhD scholarship at DTU Energy. The project will integrate innovative physics-based atomistic modeling methods and data-driven inverse molecular
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for Nuclear Research (NCBJ) is inviting applications for a position PhD student - scholarship (machine learning-driven modeling of metallic glasses) Location: Otwock - Świerk - in the outskirts of Warsaw with