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general planning of the PhD study programme, please see DTU's rules for the PhD education . Assessment The assessment of applicants will be made by Assistant Professor Raphael Ferreira together
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the experimental team co-supervise BSc and MSc student projects As part of the Danish PhD program, you will also take PhD courses, participate in teaching, conduct an external research stay, and disseminate your
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, application, and the research center, please contact Professor Joel D. Cox (cox@mci.sdu.dk ) or Professor Christos Tserkezis (ct@mci.sdu.sdu). If you experience technical problems, please contact hcm-support
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offer computational efficiency and the ability to handle uncertainties. This project aims to identify promising RL-MPCs for application and upscaling in real-life building management settings. As PhD
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, please see DTU's rules for the PhD education . Assessment The assessment of the applicants will be made by Patrick Njage (Main Supervisor), in collaboration with Frank Møller Aarestrup and Pimlapas
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programme, please see DTU's rules for the PhD education . Assessment The assessment of the applicants will be undertaken by the members of the supervisory team embracing this PhD scholarship. We offer DTU is
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for Science & Technology (KAIST), and an external stay at KAIST will be included as part of the PhD program. Qualifications Proficiency with Python Experience implementing various Machine Learning algorithms
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stability, and computational efficiency. It is expected that the coding will be done with an open-source programming language. The field experiments have the aim of validating the modelling; they will involve
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decision-making in chemical engineering research and teaching. To support this effort, we invite applications for 1-2 PhD students (3 years). You will become part of a small, cross-disciplinary team working
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proficiency in relevant programming languages (e.g., Python, C++) and tools such as ROS. Experience in simulation and digital twins, as well as the use of synthetic data for training machine learning models, is