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Science, Physics, Mathematics, Robotics, or a related discipline. A strong interest in one or more of the following areas: AI and machine learning, computer vision, signal processing, sensing, robotics, or embedded
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physics-based and data-driven methods to support the design and scale-up of these systems. This approach will reduce the need for costly experiments, improve scale-up predictions, and provide confidence
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conductance (G) and Seebeck coefficient (S) with low thermal conductance (k). Graphene Nanoribbons (GNRs) are promising but currently, designing high-ZT GNRs is a slow, trial-and-error process, as the inverse
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Electronics, will use computational simulations to study how thin films form during flowable chemical vapor deposition (FCVD), a process used to build advanced semiconductor devices. Unlike traditional CVD
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About the project: SEGregation of residual eleMENTs at austenite grain boundaries in recycled steels (SEGMENT) Supervisor: Dr Michael Auinger, University of Warwick Steel recycling is a key strategy
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molecular sensors. About HetSys: Harnessing Data, Modelling and Simulation for Real‑World Impact HetSys (Centre for Doctoral Training in Modelling of Heterogeneous Systems) at the University of Warwick is an
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to plant biosciences where the impact could be huge and as a result exciting opportunities get missed. When we use light to image deep into complex samples there is a common problem that occurs – the light