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contribute to the preparation of reports, manuscripts, and other written outputs. Requirements for both posts are: PhD in Nutrition, Epidemiology, Statistics. Expertise in data analysis: nutritional biomarkers
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, complex quantitative datasets, Experience of quantitative research related to child development, Longitudinal data analysis Additional Information Eligibility criteria Mandatory: *PhD in psychology
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. The role requires strong expertise in microbiome bioinformatic technologies (e.g., shotgun metagenomics), and advanced data analysis including statistical modelling, multi-omic integration and reproducible
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independent and team activities involved in the collection, analysis, documentation and some interpretation of information/results. To undertake tasks which may include recording results and preparing technical
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for both posts are: • PhD in Nutrition, Epidemiology, Statistics. • Expertise in data analysis: nutritional biomarkers (Post 1) • Expertise in dietary data analysis and food data (Post 2
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, computer science, artificial intelligence, or mathematics/statistics, with a PhD in one of these fields or a closely related field, and interested in applying this skillset to the analysis of music data. The place
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of qualitative and participatory data using appropriate approaches (e.g. reflexive thematic analysis), ensuring rigour, reflexivity, and alignment with project aims. To support the development and delivery of co
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recovered, transcribed, and edited within the scope of this project. The candidate’s background can be either in in traditional music analysis (with a PhD in musicology, music analysis or music theory) and/or
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, complex quantitative datasets, Experience of quantitative research related to child development, Longitudinal data analysis Additional Information Eligibility criteria Mandatory: *PhD in psychology
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management. We are looking for someone with a background in, and passion for, molecular ecology/conservation genetics, with strong bioinformatics/quantitative skills (e.g., in the analysis of NGS data