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Field
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Systems, or a related field. Strong analytical and critical thinking skills. Strong machine learning (ML), computer vision (CV), large language models (LLM) for quantitative data, texts, images, and sensor
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About Us The London Institute for Healthcare Engineering (LIHE) is part of the School of Biomedical Engineering & Imaging Sciences in the Faculty of Life Sciences & Medicine at King’s College London
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cell biology and disease modelling. The successful applicant will employ human pluripotent stem cell (hPSC)-based models and in vitro differentiation to dissect the links between chromosomal copy number
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an appropriate subject (including Computer Science, Physics, Maths, Engineering) Knowledge of modern machine learning techniques and experience with coding in Python is beneficial (but not a strong requirement
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both King's College London's School of Biomedical Engineering & Imaging Sciences (BMEIS) in the Faculty of Life Sciences and Medicine, and Guy's & St Thomas' National Health Service (NHS) Foundation
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expertise in Robotics, Lab Automation and Image Informatics. You will be also supported by a senior supervisor from Draeger. Candidates should have an undergraduate qualification in Computer and Data Science
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. About Us The London Institute for Healthcare Engineering (LIHE) is part of the School of Biomedical Engineering & Imaging Sciences in the Faculty of Life Sciences & Medicine at King’s College London. It
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–200) desirable, as well as experience in TEM/STEM image processing and simulation using open-source Python packages such as atomic simulation environment (ASE) and abTEM. A willingness to occasionally
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or on the telephone), and as such is of central importance to the image that CJBS presents. The role holder needs to actively engage with the Schools' clients, students, programme participants and visitors to deliver
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would be doing: Process and analyse large-scale calcium imaging datasets from multisensory experiments, including neural responses from visual and auditory cortices recorded over multiple days Apply and