538 postdoc-in-thermal-network-of-the-physical-building PhD positions in United Kingdom
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Field
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vegetation results in different temperatures in the sunlit and shaded areas that depend on the solar radiation, physical state of the surface, and meteorological conditions. Models that combine the simulation
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the need for sustainability to achieve Net-Zero goals. Cyber-Physical Systems (CPS) integrate machines, robots, and AGVs, but challenges like mechanical wear and electronic errors pose risks to efficiency
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, energy, and automotive. Among its variants, wire-arc directed energy deposition (WA-DED) is emerging as an increasingly compelling approach for building large-scale structural components. This process
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Are you fascinated by working at the intersection of physics and synthetic biology? This PhD project offers a unique opportunity to develop autonomous microswimmers, which are bioinspired structures
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Applications are invited for a Doctoral Candidate in SHIELD (Strategies for Healing Implant-Associated Infections and Enhancing Longevity in Devices) Doctoral Network. The candidate would be working
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the context of both demand and supply to promote sustainable built environments. Building Environment: Optimisation of buildings and built environments for thermal comfort, indoor air quality, visual / spatial
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for cardiovascular applications. You will build on our group’s expertise on Physics-Informed Machine Learning (PIML), a powerful approach that combines data-driven AI with the rigour of physical and physiological
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NPL, the UK’s national metrology institute, is developing a fully functioning, thoroughly characterised, local area quantum network (QLAN) linking heterogeneous nodes across its site. It will make
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Fully-funded PhD Studentship: Adaptive Mesh Refinement for More Efficient Predictions of Wall Boiling Bubble Dynamics This exciting opportunity is based within the Fluids and Thermal Engineering
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for cardiovascular applications. You will build on our group’s expertise on Physics-Informed Machine Learning (PIML), a powerful approach that combines data-driven AI with the rigour of physical and physiological