68 algorithm-development-"Multiple"-"Prof"-"UNIS"-"DIFFER" positions at University of Nottingham
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on paid leave during Christmas, Summer and Easter. Ongoing support to develop your skills and gain industry recognised qualifications. Personal and Career Development support, and opportunities for career
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allowance: For staff on fractional contracts- working during university term times: paid leave is paid on Christmas, summer and easter. Ongoing support to develop your skills and gain industry recognised
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over the following 9 months. Researchers from multiple UK universities have been involved in the development of the 11.7T National Facility and the appointed Research Fellows in UHF MRI/S will work with
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push the limits of multiphysics CFD for laser manufacturing by developing a next-generation simulation capability for laser drilling (with relevance to additive manufacturing). Your work will capture
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push the limits of multiphysics CFD for laser manufacturing by developing a next-generation simulation capability for laser drilling (with relevance to additive manufacturing). Your work will capture
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Applications are invited for the position of Research Associate/Fellow on Chinese development to contribute to an ERC-supported study at the Nottingham University Business School (NUBS). The purpose
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INTERNAL VACANCY This vacancy is open to employees of the University of Nottingham only. We have an exciting opportunity for a Learning Development Consultant (Access and Participation) to join our
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vital part in delivering high-quality, production-ready software to support innovative research projects in health data research. Day to day, you will design, develop and maintain secure platforms, and
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sponsored by the MTC, any successful candidate would need to pass their security checks prior to the commencement of the PhD. Motivation This project will develop an innovative co-axial water-mist-assisted
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difficult to deploy outside large data centres. This PhD project focuses on developing resource-efficient computer vision methods that maintain strong performance while dramatically reducing computation