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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
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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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. 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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to explore the regulation of mRNA modifications in developing cortical neurons. Key techniques will include biochemical approaches, fixed tissue imaging, stereotactic surgery, structural and functional
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-ranking peer-reviewed journal relating to AI, Generative-AI, Trustworthy AI, or the social impacts of AI. Delivered an agentic LLM prototype with public evidence e.g., GitHub repo, demo, or peer-reviewed
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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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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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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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treatments. To achieve this, we will develop personalised cardiac models at scale, and update these models over time, using imaging and electrical data collected by collaborators at multiple centres. We
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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