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Field
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the role Overview of the role We are seeking a highly motivated Research Fellow in Machine Learning to join the PharosAI team, focusing on developing novel machine learning methods in computer vision
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(see below). There is currently one fellowship available where the successful candidate will join one of our Cardiovascular Research Teams, details as follows: - BRC Theme: Cardiovascular / Imaging
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in NLP. Completed a PhD or equivalent qualification or research experience in machine learning, natural language processing and image processing. Emerging track record and recognition for quality
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the role Overview of the role We are seeking a highly motivated Research Fellow in Machine Learning to join the PharosAI team, focusing on developing novel machine learning methods in computer vision
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, clinicians and imaging experts from UBC, BCCRI, and our international institutional and industry partners. The fellow will work within our multidisciplinary team (medical physicists, engineers, nuclear
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. Prior experience in at least one of the following is a requirement: physiologically based pharmacokinetic (PBPK) modeling, computational oncology/biology, kinetic modeling, advanced image processing
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supportive environments. The clinical infrastructures include multiple imaging scanners, including a long axial field-of-view (LAFOV) PET/CT scanner, and aims to push the limits of modern technology. Moreover
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lab investigates how neural circuits process visual information and drive behaviour, as well as the evolutionary development of these visual systems. By studying a myriad of vertebrate species, we aim
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machine learning, statistics, logic, language technology, and ethics. You will be also part of the Digital Signal Processing and Image Analysis (DSB) group in the Department of Informatics at UiO. Francesco
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strategies that modulate the crosstalk between tumor and immune cells, and develop new image-based screening technologies to identify targets that mediate clinically-relevant cell-cell interactions