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patients with lung / cardiac MRI and improve patient experience. Image computing support for pulmonary MRI applications. Development of hardware for neonatal / paediatric MR applications Contribute to and
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. Department of Electrical Engineering and Computer Science carries out research within Computer Science, Data Science, Cybernetics, Signal Processing and Biomedical Engineering. The research network Stavanger
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, and formulation of clinical study design, image processing, machine learning, and statistical analyses to illuminate specific research questions. Among the machine learning techniques, deep learning
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developing machine learning or data science approaches for patient stratification and genetic association analyses using cardiac magnetic resonance imaging in biobank populations. Successful applicants will
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Full-time: 35 hours per week Fixed-term: 13 months The opportunity: Conduct original research on neuronal networks underlying the processing of natural visual stimuli, using in vivo large-scale two
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* Experience with image analysis or medical imaging Established record of peer-reviewed scientific publication Prior experience / comfort with computer programming is a plus Modes of Work Positions that
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, specifically in Computer Vision Proficiency in python and deep learning libraries (pytorch, Tensorflow) Preferred Qualifications: Experience in Medical Imaging (ideally in Ophthalmology) Track record
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biomedical imaging agents. The centre combines cutting-edge chemistry with clinical applications, supporting observational studies and clinical trials to advance precision medicine. The joint UCLH
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bronchoscopy programmes for patients with premalignant changes in their lung. We offer a rapid diagnostics clinic in the UCLH Macmillan Cancer Centre, which includes state-of-the-art imaging with computed
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processes that use data-driven machine learning. Given the span of the IN-CYPHER programme, we are seeking multiple motivated research fellows. Unique in its scope, we are developing technologies that span