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new types of measurements, can help us create a more complete picture of the electron wavefunction. The project relies on a combination of concepts from quantum mechanics, information theory, and
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overheating models by integrating TIR imagery with energy flux data, building physics parameters, and local weather conditions. Apply machine learning techniques for TIR and other open-source image analysis
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“black boxes,” making it difficult for regulators, engineers, and the public to understand or verify why an AV behaved in a particular way. This lack of transparency is a major barrier to certification
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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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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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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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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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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
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MRC DiMeN Doctoral Training Partnership: Exciting PhD opportunity - Cracking the RNA Code of Inflammation: A New Frontier in Ageing Research MRC DiMeN Doctoral Training Partnership PhD Research
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Applications are invited from PhD studentship candidates with good first degrees in computer science, physics, maths, biology, neuroscience, engineering or other relevant disciplines to join