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Field
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narrow down what parts of our genome are actually important for defining modern human-specific biology. This project will analyse data from these ultra-large datasets, alongside data from our great apes
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loads in power system dynamics and stability as system strength continues to decline. Building on existing frameworks such as the WECC Composite Load Model (CLM), you will develop and validate data-driven
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the elegant Georgian New Town, the beauty of Arthur’s seat and the fascinating Calton Hill; the vibrancy of the life, and the large and international student population; cultural events like the Fringe
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stability as system strength continues to decline. Building on existing frameworks such as the WECC Composite Load Model (CLM), you will develop and validate data-driven methods for load identification and
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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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for appointment at Grade 7 with a salary range of £39,424- £47,779 per annum with amended duties and responsibilities. About us The MMM Unit is based at the Big Data Institute and John Radcliffe Hospital. We work
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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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Spectrometry Facility at Birmingham; a large, multidisciplinary research team that works together operating the latest state-of-the-art mass spectrometers. The PhD will start with extensive training in the state
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visiting SRC for collaborative data processing and participating in seismic survey on the island arc. The candidate will benefit from working with a large multi-disciplinary research team recently funded by
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, medieval city with a large student community, situated at the Norfolk coast with an active pub and coffee scene. For further information and to apply, please visit our websites: https://quadram.ac.uk/about