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experimental chemistry, providing a supportive research environment. Applicants should have a PhD in Chemistry or related field, and extensive experience in python programming and machine learning models
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collaborative links thorough our collaborative network. The researcher should have a PhD/DPhil (or be near completion) in robotics, computer vision, machine learning or a closely related field. You have an
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will contribute to the development of a new simulation-based pre-training framework for building more robust and trustworthy machine learning-based clinical prediction models. Funded by the Medical
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projects in computer vision research, with a particular emphasis on Spatial Intelligence, 3D Computer Vision, and 3D Generative AI. You should hold a relevant PhD/DPhil (or near completion*) in Computer
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have: Experience with AI and machine learning for medical images Experience working with data from multiple hospitals An interest in rare disease research. Additional information Informal enquiries
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will work as a member of an interdisciplinary team (including experts in machine-learning and microbiology) to establish microfluidics-enabled microscopy assays on single bacterial cells to determine
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possess a relevant PhD in Turbomachinery (or Chemistry and) Computational Fluid Dynamics, a strong multi-physics modelling background in Machine learning, a strong record of publications, proven competence
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interdisciplinary team (including experts in machine-learning and microbiology) to establish microfluidics-enabled microscopy assays on single bacterial cells to determine their antibiotic resistance. Your work will
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for analysis of large-scale bulk and single cell data sets Strong understanding of statistical modelling, data normalisation and machine learning methods applied to biological datasets Experience with data
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data sets Strong understanding of statistical modelling, data normalisation and machine learning methods applied to biological datasets Experience with data management and version control (Git/GitHub