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fluid processes, electrical engineering, power electronics, renewable-energy control, offshore energy systems, and Power-to-X. The research environment is being further strengthened through the C-TECH
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flagship project building the next generation of semiconductor packaging – the part of chip making that decides how small, fast and powerful electronics can get. You will join a team that works with 60
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PhD Studentship: Efficient Long-Horizon Task Execution in Physical AI (deep learning, computer vision, robotics) Number of awards: 1 Award information: Fully funded PhD studentship covering Home
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Infrastructure? No Offer Description Area of research: PHD Thesis Job description:PhD Position - Quantitative Analysis of Carrier Dynamics in Operando Photovoltaic Devices Using Analytical Electron Microscopy
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performance (10–50 Hz) on hardware with constrained memory, power and compute. The project will investigate training, adapting and deploying compact Physical AI models efficiently. Work may cover vision
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the growing demand, in MINDnet will investigate neuromorphic computing as a promising solution to support such a demand by getting inspired by the brain’s powerful and energy-efficient processing capabilities
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About the project: Machine learning accelerated electronic transport calculations for complex materials Supervisor: Prof. Neophytos Neophytou, University of Warwick Advancements in materials
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consumption ecosystems? Job description If this question sparks your interest and you are motivated to pursue a PhD in circular consumption niches and the transition to circular consumption, you might be our
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deploying the face de‑identification pipeline on resource‑constrained hardware, optimizing the underlying AI models based on latency, memory, and power constraints, and building demonstrators that showcase
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? Job description If this question sparks your interest and you are motivated to pursue a PhD in circular consumption niches and the transition to circular consumption, you might be our new colleague