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plasma and iPSC-derived human disease models. You will investigate disease-related molecular signatures using metabolomics, lipidomics, proteomics and genomics, and combine these data using statistical and
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metabolomics, lipidomics, proteomics and genomics, and combine these data using statistical and machine-learning approaches. Established markers such as neurofilament light chain (NfL) and GFAP will provide a
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solid foundation in empirical research methods and applied statistics; an interest in measuring subjective and patient-reported outcomes; good analytical, organisational and academic writing skills
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, antimicrobial resistance, and ideally metagenomics or microbial genomics. Quantitative, statistical & bioinformatics skills Experience analysing complex longitudinal datasets, proficiency in R and/or Python, and