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London, with a team of investigators covering AI, computer vision, robotics, and medical imaging. You will join a dynamic and successful team with access to both cutting-edge computer power and advanced
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. The research requires experience in high vacuum systems, laser, molecular beams and laser desorption sources, charged particle beams and optics, velocity-map imaging detection, and the associated data processing
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stage of the recruitment process. Please note that this is a PhD level role but candidates who have submitted their thesis and are awaiting award of their PhDs will be considered. In these circumstances
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period of 12 months in the first instance, with potential to extend. The project involves advanced theory for new ultrafast imaging experiments and is funded by Engineering and Physical Sciences Research
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solar (thermal and PV) and geothermal energy with soil-based thermal storage to enable reliable 24/7 operation of adsorption desalination. We also develop low-cost sorption composites from locally
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of ultrasonic processing and materials characterisation. You will be specifically responsible for the testing, characterisation and critical evaluation of the as cast and prototype AM test pieces. Hence a
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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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document will provide information of what criteria will be assessed at each stage of the recruitment process. Please note that this is a PhD level role but candidates who have submitted their thesis and are
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control of image illumination/acquisition and stage movement systems. Processing and analysis of data from the above. Interacting with commercial collaborator for the translation of concepts to applied
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anion photoelectron spectroscopy (imaging) both in the time and frequency domains. The research project aims to exploit these methods to develop an understanding of electron-driven chemistry of water