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(PDRA) for the Residential Air-conditioning Demand Futures (RADFutures) project funded by the Energy Demand Research Centre (EDRC), supported by the Engineering and Physical Sciences Research Council
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publication-ready habilitation. You hold courses independently in the Bachelor programme „Languages and Cultures of South Asia and Tibet” and the Master programme “Languages and Cultures of South Asia” within
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international initiatives. To be considered, you must hold, or be close to completion of, a relevant PhD/DPhil in one of the following subjects: computational genomics, genetic or molecular epidemiology, medical
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Excellent employee health and wellbeing services including an Employee Assistance Programme Exceptional starting annual leave entitlement, plus bank holidays Additional paid closure over the Christmas period
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This is an exciting opportunity to join a cutting-edge, multidisciplinary project at the intersection of microbiology, animal health, and agricultural robotics. In a collaboration between the University of Liverpool and AG Products Ltd., you will play a key role in evaluating the impact of a...
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to learn new techniques and apply them in an interdisciplinary research environment. Application Process Applications for this vacancy are to be made online and you will be required to upload a supporting
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Longitudinal Cohort Evaluation (LCE) of participants in a campus-based STEM outreach programme . The LCE has been delivered and the drafts of reports and papers completed. The Research Officer will complete full
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This is an exciting opportunity to join a cutting-edge, multidisciplinary project at the intersection of microbiology, animal health, and agricultural robotics. In a collaboration between the University of Liverpool and AG Products Ltd., you will play a key role in evaluating the impact of a...
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for the duration of the scheme. Application Process Applications are open throughout the year. Applications received before 15 January 2026 will be considered for intake 2026. Interview by
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with the possibility of renewal. This project addresses the high computational and energy costs of Large Language Models (LLMs) by developing more efficient training and inference methods, particularly