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recently developed in a commercial 65 nm CMOS imaging process by a large international consortium of engineers and scientists for the ALICE ITS3 upgrade and the future experiments, ePIC@EIC and ALICE3@LHC
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experts to acquire bespoke training and testing data; develop prototype solutions informed by the latest ideas in medical imaging AI, computer vision and robotic guidance; and evaluate models in simulated
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cell biology; cancer; cardiovascular; nutrition and diabetes; genetics; infection and immunology; imaging and biomedical engineering; transplantation immunology; pharmaceutical science; physiology and
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at the intersection of these research areas. You should hold, or be close to completing, a PhD/DPhil in mathematics, statistics, physics, engineering, data science, or a related field. Experience in cancer
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optimisation techniques and AI-based models to support decision-making in microgrid design and operation. Working in collaboration with a leading global mission critical firm of engineers, this project offers
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at the intersection of these research areas. You should hold, or be close to completing, a PhD/DPhil in mathematics, statistics, physics, engineering, data science, or a related field. Experience in cancer
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Vitro Models. The project aims to use organ-on-a-chip technology combined with bioengineering approaches to develop, validate and use a suite of vascularised human tendon-chip models. These high quality
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experience in image data processing and analysis Familiarity with femtosecond/picosecond lasers and safe alignment practice. Clear, timely communicator who enjoys collaborating across physics, engineering and
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to answer pressing biological questions across development, cancer and immunology. We work shoulder-to-shoulder with biologists, clinicians, engineers and data scientists, providing an exceptionally
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(model performance) and quality studies (human factors assessment). You should hold a relevant PhD/DPhil (or be near completion) in computer vision or robotics or biomedical image analysis. Knowledge