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, relevant experience in computer-based statistical analysis and presentation of results, demonstrated proficiency in a coding language used for data analysis, such as Python or R, strong quantitative skills
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, biomarker, and genetics data across multiple studies. Expertise in biostatistics and familiarity with handling multiple data types, both cross-sectionally and longitudinally, are critical for success. IUSM is
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project developing Bayesian causal inference methods for mediation analysis using Electronic Health Records (EHR) data. The Research Fellow will design and implement Bayesian methods and software
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-analysis and qualitative evaluation. We are seeking a research fellow with experience in maternal health or obstetric research, conducting systematic reviews, and data collection including identifying
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in a newly outfitted robotics facility at the University of Surrey, with access to the Environmental Flow Laboratory wind tunnel facilities, gas analysis laboratories, and outdoor test spaces
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machine learning methods to the analysis of large-scale astronomical datasets, with a particular emphasis on time-domain astronomy. Research directions will be flexible and shaped according to mutual
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. Experience of the development, validation, analysis and reporting of complex decision analytic cost effectiveness simulation models. Experience of the application of advanced value of information analysis
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to be able to engage in deep critical thinking to develop theoretical insights, have excellent verbal and written communication skills, the ability to work independently and contribute positively to a
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OMICS (transcriptomics, epigenetics, metabolomics and proteomics) and cell culture will be highly considered when selecting the candidate. Background in computational analysis of the data will be highly
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Trust grant with an anticipated start date of the 1st November 2025 or as soon as possible thereafter. The project will involve experiments at Free Electron Laser Facilities and subsequent analysis and