472 computational-physics-"https:"-"https:"-"https:"-"https:" PhD positions in United Kingdom
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. This interdisciplinary PhD is ideal for candidates with a background in chemical engineering, physics, soft matter science, computational chemistry, and/or related disciplines. Early applications are encouraged, as the
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-quality simulation data. This PhD aims to fundamentally change the turbomachinery design process by replacing iterative RANS-based CFD loops with regression-driven inverse design. Instead of repeatedly
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. The project is designed to be accessible to students from engineering, physical sciences, mathematics, or data science who are motivated to apply their skills to real-world energy and climate challenges
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support After a suitable candidate is found, funding is then sought from the University of Nottingham as part of a competitive process (this will cover home tuition fees and UKRI stipend) Postgraduate
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, and travel related to the project. Overview ReNU+ is a unique and ambitious programme that will train the next-generation of doctoral carbon champions who are renowned for research excellence and
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, Aeronautical, Civil, Chemical Engineering, Applied Mathematics or Physics. Knowledge, skills: Fluid mechanics; desirable: wall-bounded shear flows, aerodynamics. Numerical analysis, in particular Computational
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mathematics, physics, or electronics and telecommunications engineering. Experience in any of the following areas is advantageous: computational electromagnetics, partial differential equations, boundary
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Experimental low-temperature physics involving nanofabrication, high pressure measurements, extreme magnetic field and milliKelvin temperatures to tune exotic low dimensional materials. Hands
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. Requirements: The candidate will have a 1st class undergraduate or Master’s degree (or equivalent) in Applied Mathematics, Physics, Aerospace Engineering, Mechanical Engineering, Computer Science, or a related
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simulate hydrodynamic and pollutant transport processes, their computational cost limits their suitability for real-time emergency decision-making. This project addresses this challenge by combining physics