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Fixed-term: The funds for this post are available for 1 year from October 2025. We are looking for a Research Assistant/Associate to join the Raspberry Pi Computing Education Research Centre in the
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replacement) project on Limits of Symmetric Computation. The position would suit a candidate seeking to obtain a PhD at the Department. The project seeks to investigate lower bounds on symmetric computation in
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developing cutting-edge computer vision and deep learning aimed at optimising inspection and monitoring of infrastructure. Applying these advanced technologies to real-world infrastructure challenges through
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position will contribute to the research programme of the recently founded "AI Hub in Generative Models", a research consortium funded by EPSRC. The goal of the programme is to do research in the area of
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of researchers who conduct cutting-edge research into NLP and AI within the University of Cambridge. Education: An excellent first degree in computer science, engineering or a closely related field Skills and
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Partnership in collaboration with Hitachi Europe Ltd, developing engineered proteins for carbon upcycling and sustainability. The role holder will collaborate with computational and biological scientists
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Biomedical Campus. You will join an exciting research programme investigating fundamental mechanisms of ribosome assembly, translational control and how defects in these processes drive cancer development
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in patient samples. We are a multidisciplinary team of molecular and functional lab scientists, computational biologists, and clinical fellows. The successful applicant will be integrated within a
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Applications are invited for two Research Assistant / Research Associate posts on the project EQUATE - a project that investigates how Natural Language Processing (NLP) could be made globally more equitable. This UKRI Frontier project was selected for funding by the European Research Council...
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animals, while Prof Durbin's works on computational genomics and large scale genome science, including the development of new algorithms and statistical methods to study genome evolution. Moving forward