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Patient Advisory Groups (PAGs), conducting qualitative interviews, running focus groups, designing and executing large-scale international surveys with quantitative data analysis, and collaborating
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FTE role supporting the international FEVER II study. C-GULL is a large contemporary birth cohort following up to 3-4,000 infants. Nested within C-GULL, HBHF is investigating early predictors of anxiety
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://aria.org.uk/opportunity-spaces/resilient-climate-and-ecosystems/accelerated-adaptation for more information on ARIA and this programme). The project is a collaboration between groups at the Universities
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, biomonitoring, and toxicity data. Key responsibilities: Lead UCAM's contribution to Task 5.2, including modelling of respiratory deposition of indoor particulate matter and estimation of exposure to aerosol-bound
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Neurodevelopment. You will develop, implement, and apply computational pipelines to analyse large-scale genomic datasets generated through Perturb-seq and other functional genomics approaches. You will use state
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for candidates to have the following skills and experience: Essential criteria 1. PhD (awarded or close to completion), or equivalent experience in human-computer interaction, AI or similar 2. Expertise
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quantitative proteomic data with a degree of statistical rigour using common freely available software packages; proficiency in handling large datasets including bioinformatics and biostatistics; and knowledge
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. This document will provide information of what criteria will be assessed at each stage of the recruitment process. * Please note that this is a PhD level role but candidates who have submitted their thesis and
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to define and evaluate AI biomarker models. You should hold a relevant technical PhD/DPhil (or near completion) in medical video analysis or computer vision with a video focus and ideally have prior
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Institute of Particle Astrophysics and Cosmology (BIPAC), on research aimed at extracting cosmological information from large-scale structure (LSS) and Cosmic Microwave Background (CMB) probes on very large