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with an international reputation for excellence. The Department has a substantial research programme, with major funding from Medical Research Council (MRC), Wellcome Trust and National Institute
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Postdoctoral Researcher: Oxford Centre for Emerging Minds Research ‘All About Me’ (Adolescent Focus)
with an international reputation for excellence. The Department has a substantial research programme, with major funding from Medical Research Council (MRC), Wellcome Trust and National Institute
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) programme . This is a fixed term position until March 2026. About STARSand HSMA and the work you will be involved with. STARS is an Open Science project that aims to increase the quantity and quality
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calculator: https://www.hw.ac.uk/about/work/total-rewards-calculator.htm to see the value of benefits provided by Heriot-Watt University. Detailed Description We are looking for a PDRA to complete the work
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. Computing time is available on our local cluster and on the Vienna Scientific Cluster (VSC), a supercomputer shared by Austria's major universities. We focus on the development of methods to solve the many
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This post is a postdoctoral research assistant role within Prof Robert House’s Group in the Department of Materials. The post will be fixed-term until 31 March 2027 (with potential to extend until 31 September 2028) in association with a new Faraday Institution-funded project entitled...
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and Prof Paul Shearing. The post is funded through a strategic research partnership and is fixed term for up to 2 years. To support the programme, the post holder will be required to carry out research
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research initiative funded by ARIA, titled Aggregating Safety Preferences for AI Systems: A Social Choice Approach. The project operates at the interface of AI safety and computational social choice, and
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and Prof Paul Shearing. The post is funded through a strategic research partnership and is fixed term for up to 2 years. To support the programme, the post holder will be required to carry out research
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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