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Field
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-critical decisions in real time. These systems rely heavily on sensor data (e.g., GPS, pressure transducers, image processors), making them vulnerable to stealthy threats like False Data Injection (FDI) and
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immobilisation, or even the chemical-physical environments thought to underpin the origin of life. This project offers a unique opportunity to work at the interface of experimental physics, data science, and
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for cardiovascular applications. You will build on our group’s expertise on Physics-Informed Machine Learning (PIML), a powerful approach that combines data-driven AI with the rigour of physical and physiological
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Applications are invited for a PhD studentship in the Department of Computer Science at City, University of London. The successful candidate will work on developing a novel AI-powered conversational
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Department/Location: Department of Engineering, Central Cambridge A position exists, for a Research Assistant/Associate in the Department of Engineering, to work on experimental investigations
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, or physics, and will demonstrate a willingness for experimental fieldwork and data analysis. This PhD offers a unique opportunity to contribute to frontier research in atmospheric chemistry, with
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factors (learning curve). These will be linked with the CCTA imaging biomarker data (quantitative plaque analysis) that is being collected as part of the EU HORIZON TARGET study to determine personalised
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. The Faculty of Population Health Sciences has established itself as UCL’s largest research-based faculty, encompassing eight institutes. More information available at www.ucl.ac.uk/population-health-sciences
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sustainable engineering strategies to boost their performance to deliver benefits for the environment and society. The outputs of this work will support practitioners in making informed investment decisions
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equivalent, in a subject relating to biology/bioinformatics/data sciences Competency in using bioinformatic software packages MRes in a relevant discipline and previous experience in handling transcriptomic