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invite applications for a limited number of fully funded PhD studentships at the School of Physics, Engineering and Computer Science of the University of Hertfordshire. This is an exciting opportunity
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define observable events based on expert knowledge and available evidence. Development of a post-race analysis structure, process and data ‘toolkit’ that can build on historical understanding of race
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develop AI- and deep learning–based computer vision tools to automatically identify and quantify intertidal organisms. Beyond computer vision, it will leverage machine learning for large-scale, data-driven
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of Science/Computer Science”. Please quote the advertised reference number ‘CENTA2026-LU07’ in your online application. During the online application process, please upload the CENTA studentship application
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Applications are invited from PhD studentship candidates with good first degrees in computer science, physics, maths, biology, neuroscience, engineering or other relevant disciplines to join
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Application ’. Use ‘Course Search’ to identify your programme of study: Search for the ‘Course Title’ using the programme code: 8856F Leave the 'Research Area' field blank Select ‘PhD in Process Industries; Net
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, the project accelerates trait data acquisition by applying computer vision to herbarium specimens and field photos, as well as large language models to extract complementary information from literature and
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, engineering, physical sciences, economics or any other field where evidence is provided of sufficient computing and mathematical background) solid experience of programming, machine learning methods and ideally
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code: 8856F Leave the 'Research Area' field blank Select ‘PhD in Process Industries; Net Zero (PINZ)' as the programme of study You will then need to provide the following information in the ‘Further
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: 8856F Leave the ‘Research Area’ blank Select ‘PhD in Process Industries; Net Zero (PINZ)' as the programme of study You will then need to provide the following information in the ‘Further Details’ section