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School of Biomedical Engineering & Imaging Sciences, King’s College London, with a team of investigators covering AI, computer vision, robotics, and medical imaging. You will join a dynamic and successful
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: analytical and forensic science; asthma and allergy; biophysics and cell biology; cancer; cardiovascular; nutrition and diabetes; genetics; infection and immunology; imaging and biomedical engineering
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, neuroscience or computer science Proficiency in Python, R, Matlab, or another relevant programming language Expertise in integrated analysis of behavioural and imaging data. Experience working with children in
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applying cutting-edge mathematical methods to spatial transcriptomics imaging data in order to describe and quantify the spatial characteristics and cellular interactions associated with colorectal response
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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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Colorectal Cancer - Stratification of Therapies through Adaptive Responses (CRC-STARS) programme, developing and applying cutting-edge mathematical methods to spatial transcriptomics imaging data in order to
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predictability and interaction with climate. Here we explore a new paradigm in which polar dynamics is typically dominated by vortices interacting across a broad range of scales, contrasting the dominance of wave
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recordings to quantify aspects of synaptic transmission in the rodent cortex. Extensive experience in performing immunohistochemistry and fluorescence imaging in rodent cortex. Extensive experience
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About the Role The successful candidate will be responsible to carry out a project in the field of Cardio-Immunology using in vivo and in vitro techniques, including flow cytometry and imaging. She
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immunohistochemistry and fluorescence imaging in rodent cortex. Extensive experience of performing in vivo gene delivery techniques in the rodent brain, such as viral delivery. Previous experience of developing custom