36 image-processing-and-machine-learning-"RMIT-University" Postdoctoral positions at KINGS COLLEGE LONDON
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About Us We are seeking experts in medical image deep learning to join our team and help develop novel computationally efficient segmentation algorithms. We welcome application from individual with
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cell biology; cancer; cardiovascular; nutrition and diabetes; genetics; infection and immunology; imaging and biomedical engineering; transplantation immunology; pharmaceutical science; physiology and
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bioinformatic workflows. Familiarity with biomedical ontologies and text mining on Electronic Health Records and biomedical literature Knowledge of machine learning / deep learning with an interest in
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access to data from AIMS-2-TRIALS, the world’s largest multimodal, longitudinal autism study; the South African BONO cohort, and the SLAM Image Bank, one of the world’s largest, real-world imaging/clinical
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research. We study the fundamental molecular, cellular, and physiological processes that underly normal and abnormal cardiovascular and metabolic function and drive the translation of this strong basic
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cell biology; cancer; cardiovascular; nutrition and diabetes; genetics; infection and immunology; imaging and biomedical engineering; transplantation immunology; pharmaceutical science; physiology and
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experience in image data processing and analysis Familiarity with femtosecond/picosecond lasers and safe alignment practice. Clear, timely communicator who enjoys collaborating across physics, engineering and
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backgrounds, including computational chemistry, bioinformatics, systems biology, and machine learning. The project offers a unique opportunity to collaborate closely with experimental scientists and contribute
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of collegiality Desirable criteria Extensive experience with confocal microscopy and live imaging Experience with biomechanics concepts and techniques such as AFM, micropipette aspiration and/or nanoindentation
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using a range of methods including cutting-edge single cell and imaging techniques. Ultimately this information will provide fundamental insights into human biology and may in the future lead to improved