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, Nulsen Genome Medicine 2021); prediction of the causal interplay between cancer genes and the immune microenvironment using statistical models (Misetic Genome Medicine 2023); development of a software for
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. This position is based in the Centre for Data Science, Statistics and Probability. Other Centres include the Centre for Combinatorics, Algebra & Number Theory, the Centre for Geometry, Analysis and Gravitation
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includes overseeing all data management processes and data linkage tasks and activities for a portfolio of projects, preparing statistical analysis plans and preparing and analysing data. The post-holder
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all data management processes and data linkage tasks and activities for a portfolio of projects, preparing statistical analysis plans and preparing and analysing data. The post-holder will work within
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. The main focus of Centre for Advanced Cardiovascular Imaging is to apply statistical, multi-omics and machine learning approaches to national-scale imaging studies. About Queen Mary At Queen Mary University
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to use statistical packages such as SPSS, Stata, R Downloading a copy of our Job Description Full details of the role and the skills, knowledge and experience required can be found in the Job Description
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collection (e.g., conducting psychiatric interviews and administrating cognitive assessments) 3. Experience of recruiting participants 4. Able to use statistical packages such as SPSS, Stata, R Downloading a
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group of Dr. Mario dos Reis, as part of a BBSRC project on development of Bayesian methods to analyse large genomic datasets. We seek a highly motivated individual with relevant background in statistics
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for candidates to have the following skills and experience: Essential criteria 1. PhD qualified in relevant subject area such as Sociology, Social Policy, Social Statistics, Management, Human Resources
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to problem solve and work independently Desirable criteria Familiarity with the JASMIN data analysis facility Expertise in the hazard of extreme heat Competence in statistical analysis and/or machine learning