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honours degree (2:1 with 65% average), or international equivalent, in Engineering, Computer Science, Physics, Mathematics, or a related discipline. Applicants should also demonstrate evidence of
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This PhD offers a unique opportunity to work at the intersection of formal methods, control engineering, and cybersecurity within the high-stakes environment of aerospace propulsion. You will be a
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-second-class undergraduate degree (or a Master's degree) in Computer Science, Mathematics, Statistics, or a closely related field Solid grounding in machine learning and/or probability/statistics
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Application deadline: 31/01/2026 Research theme: Control Engineering, Robotics UK only This 3.5-year PhD studentship is open to Home (UK) applicants. The successful candidate will receive an annual
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for applicants with a degree in Computer Science, Mathematics, Physics, or Engineering. Prior experience in AI is necessary. Prior experience in tomographic imaging and medical physics would be advantageous but
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into areas such as AI-driven verification, predictive maintenance, and compliance assurance, aiming to enhance system reliability and safety. Situated within the esteemed IVHM Centre and supported by
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PhD studentship in Computer Science: From Formal Requirements to Specification-based Automated Testing for Safety-Critical Medical Device Software Certification Award Summary 100% fees covered, and
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PhD studentship in Computer Science - Dynamic Validation of AI Systems in Digital Twins: A Real-Time Safety Framework for Critical Infrastructure Resilience Award Summary 100% fees covered, and a
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First or strong Upper Second-class honours degree (2:1 with 65% average), or international equivalent, in Engineering, Computer Science, Physics, Mathematics, or a related discipline, and demonstrate
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, and motivated to improve workplace safety in healthcare technologies and to work across research, industry, and medical engineering. Methodology The overall aim of the project is to design and evaluate