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Field
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ecology and oceanography, the project will leverage large existing datasets on (i) the movement of migratory seabirds throughout their annual cycle, available via BirdLife’s Seabird Tracking Database (STD
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-the-fitness-costs-of-drug-resistance-in-cancer for further information. The project aims include: Project aims Barcode a panel of cancer cell lines to enable genetic lineage tracing Design a large-scale
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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
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data-driven approaches, multi-scale model development and software development depending on the interest of the successful applicant. Big picture: The Tarzia Research Group (https
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spectroscopic methods suitable for large-scale sample screening and eventual field deployment. The project will also involve developing your skills in data science, including multivariate analysis, machine
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the development and implementation of machine learning (ML), computer vision (CV), large language models (LLMs), and vision-language models (VLM) to automate data extraction and interpretation for productivity
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neuroscience and data analysis Proficiency in programming (e.g., Python, MATLAB, and similar languages) Experience with large-scale neural network simulations Experience with analysing large-scale neural
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will use large genomics databases such as the UK Biobank, a collection of 500,000 individuals including genetic and healthcare records. The project is a data analysis project – from day to day you will
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. You will focus on machine learning, but will be involved in all areas. There are also spinout opportunities. For details: PhD information sheet The team have wide experience studying bumblebee behaviour
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technology (FinTech) Payment technologies and the future of money Explainable artificial intelligence (AI) in financial services Integration of FinTech and big data in financial markets and sustainable finance