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publications in medical image analysis or computer vision video analysis. Knowledge of ultrasound imaging is not a requirement but an interest in research at the interface of machine learning with real-world
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We are seeking a creative and highly motivated postdoctoral researcher to join the CAIFE study, a joint project led by Professor Alison Noble (Institute of Biomedical Engineering) and Professor Aris
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biochemical work with proteins and DNA will be highly rated in the selection process. The ideal candidate will have recently obtained a PhD in physics, biophysics, biochemistry, physical chemistry, engineering
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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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, 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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providing cutting-edge facilities, it encourages innovation and shared discovery, and benefits from the close proximity of the scientific departments as well as advanced imaging and characterisation
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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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for real-time human data processing in interactive settings. Technical expertise in areas such as electrophysiological recording, VR paradigm design, closed-loop algorithm development, or clinical