18 data "https:" "https:" "https:" "Inserm" Fellowship positions at University of London
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for an experienced researcher with expertise in health economic evaluation, health record data science, including interrupted time series approaches. Experience of infectious disease research would be an advantage
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environment. Further information on the programme is available at: PROGRAMME | CREATE PhD Programme (create-phd.org) This programme is aimed at supporting health professionals who wish to undertake rigorous
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research, etc. The post-holder will primarily undertake data extraction, data management, and advanced quantitative analyses, as well as liaising with the other research teams, supporting patient and public
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risk factors in eastern Hararghe, Ethiopia. Candidates should have a postgraduate degree in demography, epidemiology or a related field and have strong quantitative or data science skills. Further, we
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data collection and management. Proficiency in statistical analysis (e.g., R, Stata) and/or data management software (e.g., ODK, SQL) is also essential. This appointment will require regular travels
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at LSHTM. The post-holder must have a postgraduate degree in a relevant topic (ideally Medical Statistics or equivalent) and relevant experience in using regression models for data analysis and statistical
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Infectious Disease Epidemiology & Dynamics department at LSHTM to work on polio eradication. This role utilises global surveillance data for polio to inform understanding of the status of eradication and
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criteria. Please provide one or more paragraphs addressing each criterion. The supporting statement is an essential part of the selection process and thus a failure to provide this information will mean that
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mitigation priorities for the UK. Candidates should also be experienced in conducting quantitative research and applying spatio-temporal epidemiologic methods, ideally to environmental health data. Further
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consequences of vaccines against Respiratory Synctial Virus (RSV) and influenza, and communicating findings to both academic and policy communities. Using data from large electronic healthcare records