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Field
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Expertise in advanced imaging methods and molecular biology techniques Having worked with industry partners in the past Willing to work in a highly structured project environment Able to function
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on advanced machine learning applications in computational pathology, medical imaging, and clinical text analysis. They will be expected to develop deep learning models for analyzing whole-slide histopathology
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from the Department of Civil and Environmental Engineering. This position is part of an exciting research programme aimed at advancing the multi-robotic wire-arc directed energy deposition technology and
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postdoctoral research associate to join our multidisciplinary team led by Dr. Rossiter, including clinicians, bacteriologists, structural biologists and advanced microscopy and imaging specialists. The project
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that will define the CNRE. CNRE research is both computational and experimental; we work on exciting problems in diverse areas such as bio-fluid interactions, signatures, wave energy, advanced materials
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experience in data-knowledge fusion-driven dynamic modeling of complex structures, specializing in uncertainty quantification of nonlinear systems and intelligent model order reduction methods, with at least
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model for innovative medical education and a centre for transformative research. The School’s primary clinical partner is the National Healthcare Group, a leader in public healthcare recognised
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and Machine Learning, with a focus on studying geometric structures in data and models and how to leverage such structure for the design of efficient machine learning algorithms with provable guarantees
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a strong background in measurement theory and statistics, demonstrating mastery in structural equation modeling and item response theory methods. As a key member of our research team, the successful
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, multilevel and multidimensional measure of structural racism. The ideal candidate should possess a strong background in measurement theory and statistics, demonstrating mastery in structural equation modeling