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Polymer manufacturing is highly energy intensive, and achieving net zero requires more than fuel switching. This project focuses on process systems engineering for industrial decarbonisation
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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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, engineering, mathematics, physics or related field; strong programming skills; interest in ML, computer vision, robotics, embodied AI or autonomous systems; motivation for independent research and high-quality
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the energy and physical resource consumption of AI models continues to scale, there is an increasing need for new computational paradigms that draw on the efficiency and parallelism of biological
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a fully inclusive research environment, we warmly welcome applications from candidates of all socio-economic backgrounds and protected characteristics. If you wish to discuss the application process
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to simultaneously learn control policies and safety certificates—mathematical proofs that control decisions are safe. Data from system operation provides evidence that both the control and the proofs
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, purified and tested for biological activity together, in a single operation taking as little as a week. You will apply this new approach to real drug targets in cancer, working at the interface of synthetic
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this: new chemistry methods that let around 100 candidate compounds be made, purified and tested for biological activity together, in a single operation taking as little as a week. You will apply this new
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of metrology, battery materials, and ceramic processing. Building on our previous demonstrations [1], this project will begin with the fabrication and characterisation of conventional electrolyte materials using
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your nominated supervisory team during the application process and that they are aware that you wish to be considered for funding. Complete your application prior to the advertised funding deadline (see