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of DTU Engineering Technology and the Department of Electric Energy at the Norwegian University of Science and Technology (NTNU). The project will investigate coordinated operation and control of local
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that merge thermo-fluid dynamic laws, deep learning, and experimental data. A central goal is to overcome current limitations in TES operation and optimization, enabling discovery of new high-performance and
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theoretical models to describe the dynamics of quantum light sources, with the goal of understanding their behavior and improve their performance. You will work in close collaboration with the experimental team
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sensing information from key locations on the offshore infrastructure. In this regard, the research will focus on the assessment of the nonlinear structural performance utilizing reliable and
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for realistic haptic control and feedback, real-time agent-based simulation for guiding optimal work task performance. Following smart serious gaming approaches, novel artificial intelligence forecasts human
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caused by the exposure to diverse simulated weather scenarios and urban traffic loadings. Responsibilities Your responsibility is twofold. First, it is driving and performing the research efforts as
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formulation, characterization, and performance testing of packaging systems in food applications. This PhD project aims to develop, characterize, and validate bio-based food packaging materials derived from
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and operation of building HVAC systems, these technologies support both energy efficiency and flexible demand objectives. Model predictive control (MPC), which involves physics-based building energy
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dynamic community of PhD students and actively supports diversity. We are looking for a motivated applicant with good competences in operation research who wants to gain hands-on experience in cutting-edge
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, which aims to revolutionize solvent-based capture by developing an AI tool to screen over 1 billion solvent formulations. Top candidates will be selected based on performance criteria such as absorption