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will play a leading role in the analysis of large and complex genetic and electronic health records datasets with a range of Statistical and Machine Learning approaches, whilst leading a broad range of
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national and international research networks. We are looking for someone with a PhD (or near completion) in a relevant field such as machine learning, biomedical engineering, or neuroscience, with expertise
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including cold war history; nuclear politics; critical international theory; colonialism and postcolonialism; gender studies; environmental politics; critical military and intelligence studies; and
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receiving customer queries and requests for maintenance (sometimes critical and / or urgent), raising maintenance events on our CAFM (Computer Aided Facility Management) system and triaging the event
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Professional Services and in Academic Departments. While undertaking your role, you will be an agent for change, reviewing your own performance and progress, looking for opportunities to learn. You will review
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; are responsive to the changing needs of University staff, students and those of our partner NHS Health Board/Trusts; support the University’s teaching, learning and research programmes; support the University’s
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& Informatics, to work on the InteGraL project (“Interpretable Graph-Based Machine Learning”). This Leverhulme Trust funded project is focused on developing alternatives to Graph Neural Networks (GNNs). Its
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an internationally competitive track record in research and makes a significant contribution to undergraduate and postgraduate education. The Scheme would suit any GP qualified to work in Wales who wants to learn
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-levels or equivalent experience. Desirable Criteria 1. Experience of working in a similar role or environment, e.g. Higher Education. 2. Ability to speak/understand Welsh or a willingness to learn. 3
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, utilising a range of machine learning approaches, whilst leading a broad range of investigative and analytical activities. Bringing skills in biostatistics and bioinformatics, with knowledge and experience