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-radiomics, neuro-oncology, dual-energy CT and imaging-guided neuromodulation. This post is particularly focused on imaging in brain cancer with funding support from the NIHR Research for Patient Benefit
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-radiomics, neuro-oncology, dual-energy CT and imaging-guided neuromodulation. This post is particularly focused on imaging in brain cancer with funding support from the NIHR Research for Patient Benefit
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members to ensure all project deliverables are met. Undertake these responsibilities in the project: i. Conduct comprehensive literature review on NQR technology, including design approaches, scanning
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highly motivated and technically proficient Research Fellow in Control and Embedded Systems Engineering to support the development and deployment of intelligent, safety-enhanced BMS technologies within a
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arrangements. The post The Faculty wishes to recruit a Postdoctoral Research Fellow in Data Science and Data Engineering to support the work of Professor Gemma Sharp. This is a hybrid post based on the Exeter
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(Research Engineer) Bachelor/Master degree in Computer Science or a related field Proven ability to conduct independent research with a relevant publication record. Outstanding data analytics, mathematical
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translation of innovative miniature, hair-thin imaging devices we have previously developed (doi.org/10.1117/1.JBO.29.2.026002 ). These devices are designed to enable early and accurate detection of cancerous
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the Project PI. ii. Meeting the deliverables by carrying out the computational simulations and experimental studies planned for under the scope of work of the projects within the timeframe to meet the
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translation of innovative miniature, hair-thin imaging devices we have previously developed [https://doi.org/10.1117/1.JBO.29.2.026002]. These devices are designed to enable early and accurate detection
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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