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Field
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requirements: PhD degree in Computer Science, Electrical and Electronic Engineering, or related field. At least 3 years of relevant experience in computer vision, artificial intelligence, etc. Proficiency in
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, including machine learning, computer vision, adaptive data modelling, and computational imaging. The objective is to develop state-of-the-art machine learning algorithms for solving ill-posed inverse problems
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, including machine learning, computer vision, adaptive data modelling, and computational imaging. The objective is to develop state-of-the-art machine learning algorithms for solving ill-posed inverse problems
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The University of Southampton are seeking to appoint a fixed term research fellow to facilitate and deliver a programme of research on a Faraday Institution funded project: SL2FBat - Sustainable Low
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program, you will perform grant funded research developing novel algorithms or building new dynamic imaging systems that account for patient motion (breathing, cardiac, etc.) during medical imaging and
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and journals. To be involved in the mentoring of PhD/Masters/FYP students. Job Requirements: Preferably PhD in Computer Science, Electrical & Electronic Engineering, or equivalent. Background knowledge
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imaging. Within our research program, you will perform grant funded research developing novel algorithms or building new dynamic imaging systems that account for patient motion (breathing, cardiac, etc
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internationally recognised for its research in craniofacial biomechanics. Located in UCL Mechanical Engineering and supported by state-of-the-art imaging and material characterisation facilities, the lab focuses
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: Preferably PhD degree in Computer Engineering, Computer Science, Electronics Engineering or equivalent. Independent, highly analytical, proactive and a team player Excellent teamwork and verbal, written
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-quality papers in top journals and conferences. The appointees will be required to: (a) develop novel AI and XR algorithms/software for medical image analysis and computer-assisted surgery tasks; (b