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4-year PhD fellowship in the Research Programme - Deep Learning-Accelerated Crystallography Pipeline
determination by developing mathematical methods and integrating machine learning into crystallographic workflows. The successful candidate will develop theoretical and computational approaches to improve
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slowly, or act quickly but lack robust planning. Frontier models typically depend on heavy compute, cloud inference or controlled settings, limiting real-world use under compute, latency and energy
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foundation models and world models enable robots that understand instructions, interpret scenes and generate behaviours. However, most systems require huge datasets, extensive teleoperation, expensive compute
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