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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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. Supporting and mentoring graduate students where appropriate. About you You will have: PhD in mathematics, physics, data science, engineering, systems biology or a related field, or be in the final stages
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applicant will have obtained, or be close to obtaining, a PhD in Microbiology, Systems Biology, Bioengineering, Biophysics, Biotechnology, Engineering, or a related discipline, together with experience in
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basic biochemical work with proteins and DNA will be highly rated in the selection process. The ideal candidate will have a PhD in physics, biophysics, biochemistry, physical chemistry, engineering, or a
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Improving the clinical success of porous orthopaedic designs – experimental and finite element study
Improving the clinical success of porous orthopaedic designs – experimental and finite element study School of Mechanical, Aerospace and Civil Engineering PhD Research Project Directly Funded UK
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biological validation experiments. Supporting integration of biological workflows with automated imaging, manipulation and sampling technologies. Working closely with engineers and software developers
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to move the glove from a promising laboratory prototype towards a reproducible device concept ready for follow-on clinical evaluation. You will utilise your expertise in flexible electronics, additive
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assessment). You should hold a relevant PhD/DPhil (or near completion) and have publications in medical image analysis or computer vision video analysis. Knowledge of ultrasound imaging is not a requirement
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THIS VACANCY IS OPEN TO INTERNAL CANDIDATES ONLY About Us The London Institute for Healthcare Engineering (LIHE) is part of the School of Biomedical Engineering & Imaging Sciences in the Faculty
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to: Develop AI and machine learning workflows to analyse microscopy and high-content imaging data from advanced in vitro models. Build computer vision pipelines for image segmentation, tracking, phenotypic