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Field
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individuals participating in studies investigating the cardiovascular consequences of preterm birth. By combining fluid dynamics, machine learning, and advanced imaging analysis, the project seeks to develop
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multiple modalities of medical imaging (e.g. fundoscopy images, OCT scans, MRI, CT, X-ray and digital pathology). We bridge the gap between machine learning research and clinical practice through fruitful
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Engineering, or related field. At least 3 years of relevant experience in computer vision, artificial intelligence, etc. Proficiency in programming languages such as C and Python Proficiency in deep learning
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, clinical and sensor data processing, quantitative image analysis and machine learning. They will establish and maintain robust research databases and FAIR-compliant data management processes for large, multi
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and computer scientists from both Nottingham Trent University (NTU) and the University of Nottingham (UoN). The successful candidate will contribute to a work package focused on the development of a
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research infrastructure. Apply advanced statistical, machine learning and data engineering methodologies to large-scale, longitudinal datasets, contributing to innovative melanoma and skin cancer research
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strong international track record in content provenance and authenticity research spanning computer vision, watermarking, machine learning, privacy-preserving technologies and open standards. We have
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strong international track record in content provenance and authenticity research spanning computer vision, watermarking, machine learning, privacy-preserving technologies and open standards. We have
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, clinical and sensor data processing, quantitative image analysis and machine learning. They will establish and maintain robust research databases and FAIR-compliant data management processes for large, multi
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Magma Research Associates / Magma Research Fellows to develop and maintain the Magma computer algebra system (http://magma.maths.usyd.edu.au/magma/ ). These positions are based at the University