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quantum mechanical effects are typically too expensive for simulations of disordered systems like liquids. This PhD will develop and deploy the tools needed high-fidelity simulations: machine learned
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, candidates will be expected to achieve/have achieved a First class honours MEng/MSci or higher degree (or international equivalent) in: Aeronautical/Mechanical Engineering or similar STEM subjects. You need
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degree or a master’s (or international equivalent) in a relevant mathematical sciences or engineering related discipline. Background knowledge in continuum mechanics, theory of partial differential
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form of energy–e.g. electrical, magnetic, acoustic, or chemical–into mechanical motion. These swimmers are expanding the frontiers of micro-engineering and can be used in tasks such as chemical analysis
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matrix functions. These computational problems are central to many scientific and engineering applications, including quantum mechanics, materials science, and weather/climate modelling. Numerical methods
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. Entry requirements: Applicants will normally need to hold, or expect to gain, at least a 2:1 degree (or equivalent) in Mechanical Engineering, Electrical Engineering, Mechatronics and Control Engineering
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Institute, with close ties to the Department of Computer Science and Technology. Preferred skills/knowledge We are seeking a passionate and collaborative PhD student with a strong background in machine
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new types of measurements, can help us create a more complete picture of the electron wavefunction. The project relies on a combination of concepts from quantum mechanics, information theory, and
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induced damage mechanisms. This project utilises a precisely controlled mist film to minimise thermally induced damage, enabling efficient processing of advanced materials. As a PhD student, you will work
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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