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Dear Allstat Please see below for details of a 3-year fully-funded PhD studentship to develop statistical methods for the analysis of trial data at the University of Exeter. Stipends are at an enhanced rate of £17,059 (2020-21) and all Home/EU tuition fees are covered. Funds will also be available for travel and research costs. Please contact the primary supervisor (Jack Bowden: [log in to unmask]) for further information & follow the link below to apply http://www.exeter.ac.uk/studying/funding/award/?id=3753 Closing date: 2nd December 2019 PhD title: Exploiting observational data in the design and analysis of clinical trials into effective diabetes treatment. Supervisors: Prof Jack Bowden, College of Medicine and Health, University of Exeter ([log in to unmask]) and University of Bristol Dr Beverley Shields, College of Medicine and Health, University of Exeter Dr Lauren Rodgers,College of Medicine and Health, University of Exeter Location: University of Exeter Medical School, RILD Building, RD&E Hospital Wonford, Barrack Road, Exeter, EX2 5DW Project Summary: This studentship will develop novel methods to exploit observational study and patient record data to improve the design and analysis of clinical trials into Diabetes. The student will develop strong quantitative skills in Statistics & data science, as well as state-of-the-art knowledge of Diabetes, its causes consequences, and its effective treatment. Project Description In diabetes, there are many different treatment options, but little guidance regarding which drug works best for which individuals. As part of our precision medicine research, we are developing statistical models to help determine the optimal treatment for diabetes patients based on their clinical features such as age, BMI and blood biomarkers. To develop these models, we have been using data from large GP records databases and randomised controlled trials (RCTs), but both have limitations. In RCTs, patients tend to reflect a narrow, selected subgroup and not all patients adhere to the study protocol or may drop out before study completion. This hinders the interpretation and generalisability of a trial’s findings in the outside world. In contrast, observational data such as GP records have real-world relevance, but the data are messy, and many variables must be controlled for to obtain estimates comparable to those from an RCT. Despite these challenges, there is a growing interest in developing statistical methods to combine both data sources, in order to improve patient care. This PhD will explore three specific aims: 1) To develop causal inference approaches for combining observational and RCT data to improve treatment effect estimation in a trial. 2) To use these findings to further refine our treatment prediction algorithms. 3) To test updated algorithms in trial settings, incorporating real world data to further improve trial analysis and better reflect routine practice. This PhD will offer the student the opportunity to work with leading statisticians in trial methodology and a world-renowned diabetes research team. The student should have a solid grounding in Statistics and experience in handling and analysing medical data. The student will join a vibrant, diverse and world class interdisciplinary research team, including geneticists, biological scientists, mathematicians, computer scientists and clinicians, all studying aspects of diabetes and related conditions. Entry requirements Applicants should have obtained, or be about to obtain, a First or Upper Second Class UK Honours degree, or the equivalent qualifications gained outside the UK. Applicants with a Lower Second Class degree will be considered if they also have Master’s degree. Applicants with a minimum of Upper Second Class degree and significant relevant non-academic experience are encouraged to apply. Applicants must ensure that they meet the eligibility requirements of the University of Exeter. To qualify for ‘home’ tuition fee status, you must be a UK or EU citizen who has been resident for 3 years prior to commencement. All applicants would need to meet our English language requirements by the start of the project http://www.exeter.ac.uk/postgraduate/apply/english/. You may leave the list at any time by sending the command SIGNOFF allstat to [log in to unmask], leaving the subject line blank.