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About the Role This is an exciting position where applicants are invited to join a multi-disciplinary team of bioengineers, biomedical scientists, and computer scientists working together at Queen
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About the role We are seeking an outstanding candidate to work in the Process Dynamics group to contribute to advanced research in AI-driven X-ray imaging for metal alloy solidification
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crystals to large-area X-ray imagers. The research is funded by EPSRC in collaboration with the NSF. About you Applicants must hold a PhD in Chemistry, Materials Science, Physics or Engineering (or be
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soft matter, with expertise in microscopy, optical imaging, and data analysis. Experience in building and working with optical traps will be highly rated in the selection process. The project also
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progression. The Iskratsch Group , at the School of Engineering and Materials Science, Queen Mary University of London is exploiting cutting-edge mechanobiological, as well as imaging approaches2-5 with the aim
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, Engineering, or a closely related discipline. You will be a materials or physical scientist with a strong track record in applying deep learning to computer vision problems, ideally within battery
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Imaging Centre (BRIC), at the university of Plymouth and Queens hospital, Romford, London. BRIC is equipped with cutting-edge neuroscience technology, including a 3T Prisma scanner and eight human research
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for optical imaging. Experience and interest in data analysis and the ability to perform basic biochemical work with proteins and DNA will be highly rated in the selection process. The ideal candidate will hold
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About Us The School of Biomedical Engineering & Imaging Sciences has attracted multi-million pound research funding and collaborates with other universities and Faculties within KCL, the NHS
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, This opportunity allows a postdoctoral researcher to work on an industrially facing project, applying artificial intelligence (AI) methods to better inform processing to obtain high-quality engineering polymers from