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Field
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apply advanced computational tools and reproducible workflows to interrogate large-scale, liquid chromatography–mass spectrometry (LC–MS)-based comparative metabolomics datasets spanning a range of model
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evaluation of the feasibility and acceptability of a novel remote monitoring model in rheumatoid arthritis outpatient services across south-east London. KIS is a KHP-supported research programme aimed
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across scales ranging from single bacteria, single host cells, 3D in vitro models to infected hosts. We have developed new imaging technologies to visualise the interface between the host and the pathogen
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transduction and orthotopic animal models. Previous experience with CARTs, molecular cloning and animal models is essential. The post holder will join a team of scientists at ICH as well as linking with
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systems modelling teams to ensure the social science analysis is aligned with systems modelling, to develop evidence-based pathways that inform implementation and policy. The role will focus significant
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impactful observation-based analyses informing forecasting ocean and climate models. Meeting these challenges, within the European HORIZON EUROPE projects GEORGE (https://george-project.eu/ ) and TRICUSO
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set-up, and data collection and analysis. - Have the ability to analyse and interpret data using appropriate statistical packages (e.g., conducting linear mixed effects models in R). - Have experience
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quantitative techniques (e.g., NLP, classification, clustering), statistical modelling, and other computational techniques Process large scale text data sets in multiple languages Create documentation for data
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set-up, and data collection and analysis. Have the ability to analyse and interpret data using appropriate statistical packages (e.g., conducting linear mixed effects models in R). Have experience
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you The ideal candidate will have a PhD or equivalent experience in a relevant field, experience of engaged, social or qualitative research, experience of system dynamics modelling and group model