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and technology. Desirable (not essential): Research experience in sports medicine and technology (e.g. publication or final year project). Programming skills in MATLAB or Python. Application Procedure
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(computer vision technologies). The interdisciplinary nature of this PhD will require the integration of environmental science, engineering, and community science methodologies. Supervisors: Primary
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benefit from the extensive and broad expertise in AI and biomedical computing at the School of Biomedical Engineering & Imaging Sciences. The work will be done in close collaboration with a
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expertise in AI and biomedical computing at the School of Biomedical Engineering & Imaging Sciences. The work will be done in close collaboration with a multidisciplinary team at KCL, UCL and with clinicians
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or higher degree (or international equivalent) in: Mechanical Engineering, Aeronautics, Aerospace Engineering, Materials or Physics We would also like to see experience in: Mechanical experimentation, FEA
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industrial partners to deliver impacts on real world The opportunity to reshape the paradigm of power system analysis and operation The opportunity to receive training and mentoring from world-leading experts
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expertise in the design and evaluation of imaging solutions and will have an opportunity to work with scientists and engineers at Cefas. They will undertake training specific to this project including imaging
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to reshape the paradigm of power system analysis and operation The opportunity to receive training and mentoring from world-leading experts *Candidates who have not yet been officially awarded their PhD will
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-inflammation and psychiatric disorders (e.g. depression). The cellular processes underlying structural brain change include neurogenesis and gliogenesis, cell loss, changes in cell shape, synapse formation and
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results from human decision-making to inform the design of this new paradigm, and feed the results of the latter back into human decision-making to help make it more explainable. The PhD student will: (1