417 data-"https:"-"https:"-"https:"-"https:"-"INESC-TEC" PhD positions in United Kingdom
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Field
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Health emergencies, mass casualty events and disasters generate large volumes of operational, clinical and organisational data. However, these data are rarely synthesised into structured, analysable
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Nanophysics & Quantum Information group at the Faculty of Physics, and a member of the Vienna Center for Quantum Science and Technology (VCQ) – one of the largest quantum hubs in Europe – and the Austrian
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Nanophysics & Quantum Information group at the Faculty of Physics, and a member of the Vienna Center for Quantum Science and Technology (VCQ) – one of the largest quantum hubs in Europe – and the Austrian
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. The studentship will start on 1st October 2026. Project Description Project Aim To develop and validate an AI co-pilot software system integrating multi-modal radiomics data to enhance cancer detection speed and
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Are you passionate about artificial intelligence, data analytics, and cutting-edge engineering applications? Join our interdisciplinary research team and contribute to the future of Non-Destructive
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resilient. The PhD student will undertake a full research programme: interviewing participants, leading focus groups, designing studies, analysing data, developing models, designing technological, educational
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About the Project As federated learning systems become increasingly embedded in high‑stakes domains where data cannot be directly shared, such as healthcare and finance, the ability to selectively
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dives into data from online consumer feedback and the embedded environmental footprints of each stem. This project will focus on the interface between the product’s aesthetic and data-augmented generative
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from the establishment fund for Prof Gary Williamson, who recently joined Queen’s from Australia. The position is to generate data in the area of polyphenols and health and publish high quality papers
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network integration for emerging low-energy opto-electronic AI systems and beyond. The challenge: Machine learning and neural networks are super-charging the complexity of problems that computer algorithms