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) offer new avenues to tackle this problem. AI models have demonstrated strong potential in clinically relevant insights from electrical signals such as ECGs, and from cardiac imaging modalities including
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of Life Sciences, starting on 1st October 2026 under the supervision of Dr Lidia Vasilieva, School of Life Sciences. Project description: Recent technological advances have revealed a plethora of diverse
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strong scientific interests and self-motivation. They will have a degree in physics, mathematics, oceanography, meteorology, or a related science with good computing and numerical skills. Entry
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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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to apply: Please choose Electrical and Electronic Engineering Research Program and Control and Power Group, then indicate Professor Balarko Chaudhuri as a potential supervisor when making the application
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Engineering and Analytical Science Civil Engineering Computer Science Electrical and Electronic Engineering Management of Projects in Engineering Mechanical Engineering Academic requirements To be considered
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: Functional genomics and psychiatric epidemiology Clinical informatics and data harmonisation Co-production and participatory research methods Working within a cutting-edge UK-wide data infrastructure
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with mechanical testing of the alloys in hydrogen rich environments will be used. The ReNU+ CDT has hosted a number of online pre-application workshops to provide guidance on the application process
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: Advanced molecular and protein analysis Mass spectrometry-based imaging Multi-omics technologies Preclinical cardiometabolic animal models They will also gain professional development in data stewardship
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Women in Engineering Day. We are also Disability Confident Level 1 Employers and members of the Business Disability Forum and Stonewall University Champions Programme. Cranfield Doctoral Network Research