112 high-performance-computing-postdoc positions at Manchester Metropolitan University
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Join a high-performance coaching environment and help shape the future of American Football at Manchester Met. About us: The Sports department of Manchester Met University works with some of the
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to help shape and deliver this exciting new programme. What You'll Be Doing Leading the design of a future-focused, high-quality curriculum Managing the NMC and university approval processes Contributing
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psychological mechanisms underlying child and adolescent mental health Performing: Understanding adaptation to complex and high-demand environments Ageing: Exploring cognition and mobility across the life span
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effective and prioritised remediation and stakeholder communication. Experience leading and developing high-performing teams, fostering a collaborative, inclusive culture aligned to organisational goals
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institute, working with elite sporting partners in our city. Our performance programme supports and nurtures emerging talent. We support over 70 teams across more than 50 sports at our world-class facilities
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process, monitoring and analysing institutional performance, assessing risk and supporting strategy developments. We provide analysis and insight to support policy development. Working for MMU: MMU offer a
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vibrant and rapidly expanding technology sector. The University was recently awarded TEF Gold and was rated Outstanding by OFSTED. The Department of Computing and Mathematics is a successful academic
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academic researchers, data scientists, and IT colleagues to deliver secure, scalable, and high-performing data solutions across the Azure ecosystem. Implement and manage data pipelines, Lakehouse
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development interventions to improve organisational effectiveness, improve collaboration and deliver a high level of performance. You will also oversee the University's approach to talent management, ensuring
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mitigation strategies to prevent performance losses due to these impurities. We will explore both experimental techniques as well as computational models to provide feedback for designing higher efficient