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Senior Research Fellow in Clinical Epidemiology and Real World Evidence
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organization part: Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences (NDORMS)
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application closing date: 2024-07-15T12:00:00+01:00
contact: HR Team, NDORMS
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comment: We are seeking to appoint a highly qualified and dedicated Senior Researcher in Clinical Epidemiology and Real World Evidence to join the Health Data Sciences research group led by Professor Daniel Prieto-Alhambra at the Botnar Research Centre, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences (NDORMS), Oxford. You will join an outstanding, multi-disciplinary and friendly group of motivated & cutting-edge researchers where you will contribute to medical research by providing highly specialist insight and support to our dedicated team. As a Senior Researcher in Clinical Epidemiology and Real World Evidence you will generate clinical descriptions based on existing medical knowledge, handbooks and/or online resources while maintaining quality control of this process. You will lead studies on the natural history and/or epidemiology of infectious diseases, inflammatory conditions, metabolic disease and cancer using real world data. You will work within the multidisciplinary team to deliver the strategic aims of the group and the delivery of the trial portfolio of studies according to time and target, you manage your own academic research and administrative activities and contribute ideas for new research projects and income generation. You will have a degree in Medicine together with a PhD (completed or close to completion) in Epidemiology, Public Health, Biostatistics, Data Sciences, or a related field. You will be able to write clinical descriptions based on existing medical knowledge together with good ability to write up study reports, manuscripts, and abstracts. Knowledge of R (or other statistical package) programming, interest in academic clinical, epidemiological or health data science research and strong attention to detail are essential. Understanding of real world data governance and methods, knowledge of the OMOP Common Data Model and evidence of previous participation in research are desirable. This is a full-time fixed-term appo…
salary: Standard Grade 8: £45,585 - £54,395 p.a.
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further particulars: JD_173885
application opening date: 2024-07-01T09:00:00+01:00
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value: _________________________________________________________________________ Summary Job title Senior Researcher in Clinical Epidemiology and Real World Evidence Division Medical Sciences Division Department Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences Location Botnar Research Centre, Old Road, Headington, Oxford, OX3 7LD Grade and Salary Grade: 8 £44,585 - £54,395 p.a. Hours Full time Contract type Fixed term for 2 years in first instance Reporting to Dr Albert Prats-Uribe Vacancy reference 173885 The role Project details The Health Data Sciences section at the Botnar Research Centre is involved in a number of national and international studies exploring the conditions of use (adherence, compliance, off and on-label use) of a number of licensed drugs, devices, and vaccines for the prevention and treatment of human disease in 'real world' (routine practice) conditions. We collaborate with researchers from around the globe to improve our understanding of the safety and effectiveness of new and long-licensed medications and devices for the prevention and treatment of arthritis, osteoporosis, infectious disease/s, cancer, and other conditions. We are also studying both the benefits and the potential risks of the use of such health technologies in special subgroups of the population under-represented in previous trials. Our research team has four key areas of research: a) To study the descriptive epidemiology of multiple diseases as represented in real world data, including primary care records, hospital records, and health claims b) To characterize the use of vaccines, medicines, medical devices and surgeries in real world (routinely collected) data c) To compare the (beneficial and harmful) effects of vaccines, medicines, devices and surgeries when used in actual practice conditions d) To characterize the presentation and treatment of multiple conditions using routinely collected health data (electronic medical records and health claims)…

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