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Field
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the foundation of computer vision, monitoring, and control solutions. However, real applications of AI have typically been demonstrated under highly controlled conditions. Battery assembly processes can be
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Engineering, Computer Science or related disciplines. Experience in autonomous system, manufacturing/robotics and machine vision development will be an advantage. To apply please contact the supervisor, Dr Kun
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Engineering Department Location: Newport, Shropshire TF10 8NB Salary: £35,166 per annum Post Type: Full Time Contract Type: Fixed Term - Until 30 September 2028 Closing Date: 23.59 hours BST
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point of this project is the opportunity for the successful applicant to work within the Centre for Computational Engineering Sciences, a leading hub for research and education in computational methods
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, requiring large computational effort to assess and study system stability. This is becoming even more challenging under increasing complexity requiring detailed dynamical models and with new dynamic phenomena
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the growing demand for sustainable AI-enabled systems, this PhD brings together low-power computing, energy-aware design, and thermal optimisation. You’ll work with advanced profiling tools, prototype long-life
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Chemistry, Physics, Chemical Engineering or Material Science. Solid knowledge in Physical Chemistry and Surface Science. Pre-knowledge on programming and Molecular Simulations (MD or MC) are desirable. Only
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temperature stability and spatial resolution, to make a leap in this field. The PhD research programme will squarely address these challenges. The PhD candidate should have completed (or about to complete
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select 'Mechanical and Manufacturing Engineering' under ‘Programme’. Please quote the advertised reference number, ‘FP-CTS-2025’, under the ‘Finance’ section of your application. Please note that 1 January
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post-mortem tissue analysis to validate findings in a clinically relevant context. The successful candidate will benefit from a multidisciplinary environment, combining Dr Fulton’s expertise in brain