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Applicants should have a first or second-class UK honours degree or equivalent in a relevant discipline such as engineering, physics and mathematics. Prior experience in fluid networks modelling is beneficial
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with engineering, physics, mathematics, acoustics, fluids, electronics or instrumentation background. Prior experience in computational modelling is beneficial, but not mandatory. Similarly, experience
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exceptional environment for students from physical sciences, life sciences, mathematics, statistics, and engineering. HetSys specializes in applying advanced mathematical methods to tackle complex, real-world
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of Heterogeneous Systems (HetSys), based at the University of Warwick, is an exceptional environment for students from physical sciences, life sciences, mathematics, statistics, and engineering. HetSys specializes
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from physical sciences, life sciences, mathematics, statistics, and engineering. HetSys specializes in applying advanced mathematical methods to tackle complex, real-world problems across a variety of
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, mathematics, statistics and engineering backgrounds who are passionate about applying their mathematical expertise to tackle complex, real-world problems. By fostering these skills, HetSys trains the next
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involve collaboration with our industrial partners. Projects provide a unique research and training experience and an exciting opportunity for you to develop mathematical innovation inspired by contemporary
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second class UK honours degree or equivalent in a related discipline, such as computer science, mathematics, or engineering. The candidate should be self-motivated and have excellent analytical, reporting
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manufacturing (year 1) - Advanced Composites manufacturing using energy absorbing fibres and nanomaterials (year 1) - Analytical/mathematical modelling and FEA modelling of hyper-velocity impact test of
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equivalent in a relevant discipline such as aerospace engineering, mechanical engineering, electrical engineering, computer science/engineering, applied physics/mathematics, or related fields. Prior experience