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will receive: Generous annual leave: 35* Days Annual Leave (pro rata if part-time) plus Bank Holidays* & Closure Days* Generous pension scheme Cycle to Work & Electric Car Scheme Employee Assistance
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+ inclusion (Stonewall Diversity Champion) and as a Disability Confident employer. We are proud signatories of the Armed Forces Covenant and welcome applications from service people. Further information Before
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with epilepsy across multiple NHS hospitals. They are expected to have some experience working with NLP in general and LLMs in particular. They will also help to further develop machine learning models
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working with NLP in general and LLMs in particular. They will also help to further develop machine learning models to predict clinical outcomes. Familiarity with current methods in this area is essential
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(STFC, Daresbury), Prof. Jonathan Tennyson (University College London) and Prof Michael Charlton (Swansea). The Research Fellow will work on the development of methods and computer programs adapted
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are proud signatories of the Armed Forces Covenant and welcome applications from service people. Further information For further information please contact Jordi Solana, e-mail j.solana@exeter.ac.uk
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. Our pre-covid NSS scores for overall satisfaction was above 90% for eight years and since covid have been ahead of the sector average and sector benchmarks. We provide a learning experience of the
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are proud signatories of the Armed Forces Covenant and welcome applications from service people. Further information For further information please contact Jordi Solana, e-mail j.solana@exeter.ac.uk
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the potential to impact on protected groups and take appropriate action. Desirable Skills: Experience with machine learning or natural language processing. Knowledge of econometric methods for policy evaluation
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: To create a world class visitor and learning experience across all V&A sites and collections. Focus and deepen the relevance of our collections to the UK creative and knowledge economy. Expand the V&A's