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your motivation to study this PhD project and your CV. For more information on the group visit: www.deboresearchgroup.com Contact Prof. Guillaume De Bo: guillaume.debo@manchester.ac.uk
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use generative AI to establish a large reference microscopy images dataset of healthy oral mucosa. The project aims to develop AI models that replicate the appearance and structure of healthy oral
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melanogaster. This project will take the next big step: moving from finding sexually antagonistic genes to uncovering what makes them special, how they affect fitness and life history traits, and the molecular
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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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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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(mammalian cell culture, lentiviral transduction, flow cytometry and FACS, Illumina sequencing and bioinformatic data analysis. You should have (or be close to completion of) a PhD in molecular/cell biology
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Start date 1 October 2026 Additional Funding Information This project is awarded with a 4-year Norwich Research Park Biosciences Doctoral Training Partnership PhD CASE studentship with Inspiralis Limited
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create a working framework that includes both experimental and modelling prototypes, including AI/ML tools to assist with the large number of variables involved. This project is seeking candidates with a
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by detecting and predicting threats such as pests, diseases, and environmental stress in line with the UK Plant Biosecurity Strategy. The project harnesses computer vision, deep learning, and large
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ability to evaluate fossil fuel CO2 (ffCO2) emissions is currently limited. ‘Bottom-up’ emissions estimates, based on inventory-style accounting and mobile tracking data, can differ significantly from each