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We are seeking an ambitious and highly motivated postdoctoral researcher to help develop the next generation of fibre-based optical imaging and spectroscopy tools. This EPSRC-funded role is central
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the supervision of Prof Amedeo Chiribiri within the Department of Cardiovascular Imaging, School of Biomedical Engineering & Imaging Sciences, King’s College London. About The Role Applicants should be medically
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interpretation. This role will involve working closely with civil engineers, computational modellers, Physicists, and geophysicists to translate raw sensor outputs into actionable insights. Role Summary Lead data
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Engineering, Data Science and AI theory and practice, ensuring their co-evolution and competent adoption across disciplines to enable transformative, interdisciplinary, impactful data-intensive research
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the supervision of Prof Amedeo Chiribiri within the Department of Cardiovascular Imaging, School of Biomedical Engineering & Imaging Sciences, King’s College London. About The Role Applicants should be medically
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excellence in Data Engineering, Data Science and AI theory and practice, ensuring their co-evolution and competent adoption across disciplines to enable transformative, interdisciplinary, impactful data
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Resonance (NMR) Experience with experimental NMR techniques and methods for imaging and spectroscopy and an ability to contribute to developing new methods Experience in pulse programme design desirable
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the results of this project. Candidates must possess a good first Degree (or Master's) and PhD (or near competition) in Engineering, Mathematics, Physics, Computer Science, or related disciplines. Your working
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Applications are invited for the prestigious Eric and Wendy Schmidt AI in Science Fellowships, a program of Schmidt Sciences, commencing 1 September 2026. This 1-year appointment at Imperial College
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publication and contribution to conferences in the field of cognitive neuroscience, physical activity, data science, engineering, brain imaging or related fields. Expertise in analysing MRI and fMRI Brain