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Field
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Overcoming the Terascale Design Challenge: Next-Generation Efficient AI for Discoveries in Surface Science and Catalysis research project, an ambitious research programme establishing a next-generation
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innovators ready to establish, grow or scale a distinctive programme. We welcome candidates from academic and non-academic routes, including industry, government, policy, technology and professional practice
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and journals. Mentor graduate students and support research activities within SNAIC. Required Qualifications Applicants should possess: PhD/Ms/BSc in Computer Science, Artificial Intelligence
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. You will be expected to undertake a self-directed program of research and scholarship, play a role in the national and international Mathematics community, in addition to teaching students
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to establishing an academic career in nuclear science or engineering. You will be responsible for: Plan, develop and conduct world-leading research Win external funding for research Supervise postgraduate and
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ambition in their ideas, and want to develop potentially transformative, high-impact research. The Fellowship is an excellent stepping stone to establishing an academic career in nuclear science or
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close to completing a PhD in labour economics or a relevant social science discipline and have a clear research focus on employment or labour markets. You will have strong applied quantitative research
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(for Research Engineer) with expertise in Computer Science, Artificial Intelligence, Computer Vision, Machine Learning, Robotics, or a closely related field. Experience in developing, training, validating and
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the Electrochemical Engineering Science Group and work within Dr Daniel Niblett's team on the five-year UKRI EPSRC ION-H2 Fellowship. The programme combines computational modelling, machine learning
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. This would normally be supported by relevant professional experience and/or a postgraduate qualification, such as a Master’s degree or PhD, in Computer Science, Information Systems, Engineering, Mathematics