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Field
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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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other duties relevant to the programme of research. Job Requirements: PhD degree or at least 8 years working experience in Computer Engineering, Computer Science, Electronics Engineering or equivalent
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neuroimaging experiments, proficient in image processing and programming paradigms. The successful candidate will contribute to ongoing multidisciplinary research and play an active role in developing novel
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, engineers, computer scientists, nuclear medicine physicians, …) towards the overall aim of enabling translational and physician-in-the-loop AI for medical imaging. Our research team is multicultural and
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experience in electrochemical sensor technologies, including surface chemistry, functionalisation, and biomarker detection Proficiency in signal processing, prototype design and integration, and
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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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blot, immunofluorescence) Cell transfection Mechanical testing and biomaterials characterization Quantitative image analysis Computational skills including data processing and statistical analysis Prior
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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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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