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include the modification of existing optimization procedures to explore the potential energy surface of materials in search of transition states and structural transformations using existing and newly
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been shown to accelerate and improve the training procedure of SNNs by defining new cost functions that are differentiable and easier to optimize. They can also handle quantized weights, e.g., using
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workshops as a means to continuously improve technical and theoretical knowledge. Ability to obtain information from literature and from colleagues and integrate this into developing and optimizing work
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research which combined efficient optimization and sequential reliability assessment. The project is funded through an EPSRC call to accelerate research outcomes to achieve a prosperous net-zero and is
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optimizing their performance in high-energy-density applications. The coated LFP materials should exhibit superior mechanical and chemical resilience, ensuring that the coatings maintain their structural
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tools that enable optimal design and operation of greener vessels, backed by real-world demonstrations. The successful candidate will work at the intersection of multi-disciplinary modelling, advanced AI
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researchers to join a dynamic team working on an EPSRC-funded project, focused on both catalytic ammonia combustion and optimal design of innovative catalytic burners for real-world industry applications. As a