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writing scientific papers. The developed models will be tested on data from energy investment models, as well as transport infrastructure problems. We will be an academic team of three PhD students and four
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performs theoretical, numerical, and experimental research in the field of manufacturing engineering. It covers a wide range of manufacturing processes and modelling approaches, metrology at all scales
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the experiments. You will also have the opportunity to carry out your own simulations with our numerical model. Qualified applicants must have: A strong drive to move the frontiers of science. Ample experience with
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strategies for conventional HVAC systems that condition entire indoor spaces using existing thermal comfort models, which could improve the performance of existing buildings and HVAC systems. The work will
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interdisciplinary team, you will break new ground at the absolute frontier of what is possible. Responsibilities Your overall focus will be to evolve and then engineer non-model autotrophic bacteria for expanded
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, modelling, optimization and validation, and focus on: Develop thermally integrated storage and conversion systems, including Carnot batteries and/or high-temperature heat pumps based on power cycles. Design
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models Tough bio-inks for surgical procedures We are looking for candidates with a high degree of independence and a strong drive for scientific excellence. These positions provide excellent opportunities
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for industrial decarbonization with emphasis in system development, modelling, optimization and validation, and focus on: Develop thermally integrated storage and conversion systems, including Carnot batteries and
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language models (LLMs) for educational purposes. Furthermore, the right candidate has a deep understanding of pedagogical research, with focus on how educational processes can be facilitated by AI. The role
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spatial variability of soil health. You will be contributing to specifically the area of using proximal and remote sensors, soil physical, chemical and biological data, as well as plant and weather data