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Position: Research Fellow/Senior Research Fellow
Institution: University of Leeds
Location: Leeds, West Yorkshire, United Kingdom
Duties: Working with and in support of Professor Philip Conaghan to ensure projects are successfully completed. Preparing papers for publication. Contributing to the management and manipulation of data to prepare analytic cohorts, in collaboration with colleagues and in line with data management policies and data protection legislation. Developing research and analytical protocols. Applying appropriate statistical methods, concepts and software to undertake analysis of data from large patient datasets. Participating in the interpretation and writing up of analyses in an appropriate and timely manner
Requirements: A PhD in a relevant subject area (including, but not limited to health data, epidemiology, statistics) or significant research experience. A track record of first author publications. Proven ability to write to the standard required for research reports/international publications. Experience in biostatistics, epidemiology and/or data analysis. Knowledge of statistical principles and statistical techniques. The ability to independently prepare clear detailed analytical protocols and to apply new statistical approaches and methodologies. Experience of leading research projects. Working experience in processing, manipulating, analysing and modelling large datasets, whilst appropriately handling missing information
   
Text: Research Fellow / Senior Research Fellow Are you an ambitious researcher looking for your next challenge? Do you have a background in analysis or epidemiology and experience with large datasets? Do you want to further your career in one of the UK’s leading research intensive Universities? We are seeking to appoint a talented (Senior) Research Fellow to work with the Osteoarthritis Research Group within the Leeds Institute of Rheumatic and Musculoskeletal Medicine. One of the major areas of research within the Osteoarthritis Research Group is the development of patient phenotypes to improve early diagnosis, prediction of response to treatment and targeted interventions. This project will utilise a 5000 patient, longitudinal cohort of early and progressive knee OA populations with the aim to explore the relationships between MR imaging features and clinical disease progression. The post-holder will work alongside our statisticians. A key component of the role will involve leading on the write-up of projects and the preparation of manuscripts for submission to peer-reviewed journals. The post-holder will report to Dr Sarah Kingsbury and Professor Philip Conaghan. Applicants should have a proven ability to write scientific manuscripts, a postdoctoral qualification (MSc or PhD) or significant research experience, and experience in biostatistics, epidemiology and/or data analysis. Experience of analysing large, datasets and knowledge of statistical packages such as Stata would be advantageous. Based at Chapel Allerton Hospital this post is available immediately for a fixed term of one year, with the possibility of extension dependent on funding. To explore the post further or for any enquiries you may have, please contact: Dr Sarah Kingsbury, Osteoarthritis Strategic Lead Tel: 44 (0)113 392 4878, email: S.R.Kingsbury@leeds.ac.uk . Further Information The University of Leeds is committed to providing equal opportunities for all and offers a range of family friendly policies. The University is a charter member of Athena SWAN and holds the Bronze award. The School of Medicine gained the Silver award in 2016. We are committed to being an inclusive medical school that values all staff, and we are happy to consider job share applications and requests for flexible working arrangements from our employees. Location: Leeds - Chapel Allerton Hospital Faculty/Service: Faculty of Medicine & Health School/Institute: Leeds Institute of Rheumatic & Musculoskeletal Medicine (LIRMM) Section: Section of Musculoskeletal Imaging Category: Research Grade: Grade 7 to Grade 8 Salary: £32,548 to £47,722 p.a. Working Time: 100% Full time equivalent Post Type: Full Time Contract Type: Fixed Term (For 1 year due to external funding) Closing Date: Thursday 08 February 2018 Reference: MHLRM1079 Downloads: Candidate Brief
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