68 engineering-computation "https:" "https:" "https:" "https:" "The University of Manchester" positions at University of Greenwich
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for Engineering, Robotics and Automation, Computer Engineering, and Electrical and Electronics Engineering. The successful candidate will contribute across the School of Engineering but will play a leading role
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School of Engineering Location: Greenwich Campus Salary: £38,784 to £55,755 plus £4228 London weighting per annum Contract Type: Permanent Release Date: Tuesday 10 March 2026 Closing Date: Monday
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). The successful candidate will become a member of the Computational Science and Engineering Group (CSEG) and will join a team with extensive expertise in computational materials modelling and phase transformation
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School of Engineering Location: Medway Campus Salary: £32,080 to £37,694 per annum Contract Type: Permanent Release Date: Monday 16 February 2026 Closing Date: Sunday 01 March 2026 Interview Date
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collaborators at University of Manchester and City St George’s, University of London. This is an exciting opportunity to contribute to the understanding of what works to support some of the most vulnerable young
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across the university. Our digital mission is to ensure everyone in our community is equipped to effectively use digital services, data and technology with confidence, efficiency and creativity in
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, the REF, and with collaborators at University of Manchester and City St George’s, University of London. This is an exciting opportunity to contribute to the understanding of what works to support some of
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School of Engineering Location: Greenwich Campus Salary: £38,784 to £55,755 plus £4228 London weighting per annum Contract Type: Permanent Release Date: Monday 12 January 2026 Closing Date
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across the university. Our digital mission is to ensure everyone in our community is equipped to effectively use digital services, data and technology with confidence, efficiency and creativity in
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-time, large-scale data demands of IIoT and lack sustainability considerations, such as energy efficiency. This research proposes a sustainable, high-performance IDS that leverages digital twin technology