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, or reinforcement learning Proficiency in Python and contemporary software ecosystem for optimization, dada management, and API development Experience with teaching and supervision Experience with IoT, edge computing
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institutes, and industrial partners across Europe to deliver a world-class doctoral training programme in risk assessment, resilience engineering, and smart technologies. Its scientific vision targets: (1
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study programme, please see DTU's rules for the PhD education . Assessment The assessment of the applicants will be made by Senior Researcher Manuel Gesto Rodriguez and Professor and Head of Section Per
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competences within computational modelling, optimization and integration of thermal energy storage technologies – such as large water pits and phase change material storage. You will work with colleagues, and
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airborne geophysical observations, and strong competences in Arctic fieldwork logistics. The gravity research group has carried out airborne gravimetry since the 1990s and has an annual work programme to
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; characterization of supramolecular polymers, their assembly, triggered disassembly, structure and properties. Active dissemination of the results obtained, in scientific articles and through participation in
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explored using scientific machine leaning. Machine learning, programming experience and a curious mind-set You are fascinated by how computers can learn from data and you have a strong interest in the
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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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Job Description Are you passionate about sustainable innovation, food safety, and creating real-world impact through cutting-edge materials science? Do you want to help design the future of food