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project focused on systematically exploring the impact of the exposome on complex disease risk, through the lens of multi-omics data (e.g., genomics, proteomics, metabolomics and biochemistry) from large
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member of the ‘Blackholistic’ team (Oxford-Amsterdam-Radboud) which includes relativistic simulations on all scales from black hole to large scale jets, as well as analysis of data from the Event Horizon
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novel data analysis and statistical methods for Type Ia supernova cosmology, and contributing to data acquisition and spectroscopic follow-up of upcoming large transient surveys (e.g. Rubin/ATLAS) using
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capabilities o Demonstrated experience with machine learning and/or statistical modeling o Expertise in handling large-scale, complex datasets with strong data wrangling skills o Strong publication record
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data assets, and in the context of the world’s largest longitudinal population studies, many hosted here at the Big Data Institute, as well as other international initiatives. To be considered, you must
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experience handling large quantities of clinical or non-clinical real-world data, preferably in a data manager role Experience applying statistical and data science techniques to address real-world clinical
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on proposing for, and analysing, data with VLBI arrays to study relativistic jets from black holes. They will work with other observers and theoreticians to develop our understanding of black hole jet formation
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. This will involve analyzing sequence data from bacterial isolates collected during a clinical trial combined and from large scale lab evolution experiments. The postholder will work as part of a large team
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forefront of AI and ethics. The role focuses on innovative research into the ethical governance of Large Language Models (LLMs), as part of the prestigious Divirsibus Vis Plurima Solvo project. This is a 2
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2 Oct 2025 Job Information Organisation/Company DURHAM UNIVERSITY Research Field Physics Researcher Profile Recognised Researcher (R2) Established Researcher (R3) Country United Kingdom Application