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at Cranfield University within a supportive, cross-disciplinary environment spanning energy systems engineering, computational modelling, bioinformatics and food safety science. The studentship is funded by
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. The candidate should have a good 2.1 Bachelors, or Masters degree in Electronic Engineering, Computer Sciences or equivalent. Experience in communications and networking, AI, or robotics is desirable but not
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integrating machine learning, computational modelling, and experimental validation. The successful candidate will receive training in both computational and experimental biology within a highly collaborative
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. The project focuses on power-aware computing, thermal optimization, and sustainable electronic design, targeting critical applications in aerospace, healthcare, and industrial automation. Hosted by the renowned
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are part of the programme. Entry requirements Applicants should have a first or second class UK honours degree or equivalent in a related discipline. This project would suit students with an aerospace
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scheme. Access to approximately 40 industrial, government & research partners from the wider aviation sector as part of the Net Zero CDT programme. Access to world class research and education facilities
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This studentship is fully-funded by an EPSRC Industrial Doctoral Landscape Award in partnership with AWE plc. The successful applicant will be welcomed into our world-leading research programme
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and determination? We are currently seeking a/an University assistant predoctoral - PhD Position in Graph Learning 39 Faculty of Computer Science Startdate: 01.05.2026 | Working hours: 30 | Collective
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Resilience (WIRe). The WIRe programme offers a bespoke training programme in technical and personal skills, access to world-leading experimental facilities. The successful candidate will also have the
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Are you an outstanding and ambitious engineering or computer science graduate looking for the next challenge? Do you want to work at the frontier of artificial intelligence and robotics to enable