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). This consortium pulls together expertise from all over the University, including in diagnostics, data science, drug and vaccine design, preclinical testing and clinical testing and brings it to bear on tuberculosis
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imaging and spectroscopy. Experience with data analysis or the ability to perform basic biochemical work with proteins and DNA, e.g., fluorescence labelling, enzymatic reactions will be highly rated in
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candidate will hold a PhD in physics, biophysics, physical chemistry, engineering, or a related area, or have submitted a PhD thesis prior to taking up the appointment. The research requires strong interest
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The post-holder will join a team of investigators working on the NERC-funded Large Grant ‘Ex-X’ Expecting the Unexpected. Understanding ‘dangerous’ volcanic transitions’, led by Prof. Jenni Barclay
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completion of a PhD in Psychology or a relevant area along with experience of collecting data from research participants. With excellent data analytic skills, you will be familiar with SPSS and at least one
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, including molecular clouds (properties, formation, evolution), dynamics (supermassive black hole mass measurements, gas flows, active galactic nucleus feedback), and any other facets of the data not yet
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especially suitable for someone with strong formal reasoning and data analysis skills who is considering progression to a PhD or further postdoctoral research in AI ethics, social choice theory
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to determine the activators of inflammation in atherosclerosis. You will identify and develop suitable techniques, and apparatus, for the collection and analysis of data (e.g. flow and mass cytometry, confocal
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DPhil students, manage data analysis pipelines, and contribute to publications and grant writing. This post is ideally suited to someone aiming to secure a long-term fellowship and build an independent
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on and defensive mechanisms for safe multi-agent systems, powered by LLM and VLM models. Candidates should possess a PhD (or be near completion) in Machine Learning or a highly related discispline. You