69 affective-computing-"https:" "https:" "https:" "UCL" positions at University of Bath
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), you’ll play a pivotal role in delivering the University’s Strategy—leading transformation projects that create real, lasting impact across our academic and professional communities. Be part of a team
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Machine Learning Research Group within the Department of Computer Science. Further information This post is a full time, fixed term contract for two years, with a potential extension to three years
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talent function that operates within the wider recruitment team. Yet there's still tremendous opportunity to make an impact, bringing fresh ideas, learning from experienced colleagues, and contributing
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also very rewarding as you will be involved in supporting the delivery of a wide range of Team Bath Netball activities including: our Performance Pathway programme our network of Athlete Development
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: to recruit senior level policymakers and decision-makers from central and local government and the third sector to the IPR Policy Fellowship Programme to facilitate a tailored programme of meetings with
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, Innovation and Research Impact, HR, our Digital, Data and Technology (DDaT) department and others, fostering an integrated approach to achieve the University’s ambitious goals. About you Proven experience
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an engaging experience and a supportive programme. About you Our ideal candidate will hold a PhD or equivalent in a relevant discipline, along with a UG degree or equivalent experience. They will be a
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an international reputation for teaching and research that develops theory, policy and practice in relation to education internationally. We offer one undergraduate programme (Education with Psychology) as well as a
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stakeholder partners, data collection and analysis, and disseminating findings to create impact. This is a key role in a major new programme of social science research, funded by a philanthropic organisation
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on cosmological simulations of galaxy formation to study the impact of feedback processes and how they manifest themselves observationally, with an aim of calibrating and improving the interpretation