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Job description
We are looking for a Research Assistant to join Unit for Medical Statistics (UMS) in the School of Life Course & Population Sciences. The main duties of the postholders will be to take day-to-day responsibility for the statistical aspects of specific studies such as clinical trials and/or other clinical studies and registry projects (epidemiological studies). This will include project planning and protocol development, study conduct, plans for all statistical analyses and liaising with the appropriate multidisciplinary teams to represent the statistics view and role. In addition, the postholder will contribute to statistical consultancy as part of UMS. All work will be supervised by a senior member of UMS.
The post holder will be graduate in mathematics/statistics (or other quantitative discipline) with strong programming skills and good attention to detail. It will suit a recent graduate with ambitions to work in medical statistics and/or clinical trials.
This post will be offered on a fixed term contract for 24 months
This is a 100% full time equivalent / 35 hours per week
Key responsibilities
• With senior statistical oversight: to take responsibility for the statistics of a number of studies. This will include some or all of: contributing to design, data form design, writing statistical analysis plans, undertaking statistical analyses, writing reports and papers, solving statistical problems that may arise, with support from senior colleagues.
• To contribute to the UMS statistical consultancy service across King’s, with appropriate training and support, as needed.
• Contribute to study reports and publications, and proposals and applications to external bodies for funding purposes as appropriate
• Attend and contribute to relevant meetings
• Identify and solve specific statistical and methodological problems that arise in collaboration with senior statistical colleagues
The above list of responsibilities may not be exhaustive, and the post holder will be required to undertake such tasks and responsibilities as may reasonably be expected within the scope and grading of the post.
Skills, knowledge, and experience
Essential criteria
1. BSc/MSc in mathematics/biostatistics (or quantitative discipline)
2. Knowledge and experience of various statistical packages such as R, Stata, Python
3. Ability to adapt statistical methodology to specific research studies.
4. Able to verbally communicate highly complex and sensitive information effectively
5. Enthusiastic and effective communicator of statistics to colleagues of all disciplines
6. Highly motivated, hardworking, adaptable, problem-solving
7. Able to multi-task and prioritise workload
8. Takes initiatives and can work independently as needed
9. Committed to equality, diversity and inclusion, actively addressing areas of potential bias
Desirable criteria
10. Experience in analysing clinical research data
11. Advisory or consultancy experience
12. Writing manuals and protocols
Candidates are strongly encouraged to specifically address the essential criteria outlined in the Person Specification in their covering letter.
Further information
The School of Life Course & Population Sciences is one of six Schools that make up the Faculty of Life Sciences & Medicine at King’s College London. The School unites over 400 experts in women and children’s health, diabetes, nutritional sciences, population health and the molecular genetics of human disease. Our research links the causes of common health problems to life’s landmark stages, treating life, disease and healthcare as a continuum. We are interdisciplinary by nature and this innovative approach works: 91 per cent of our research submitted to the Subjects Allied to Medicine (Pharmacy, Nutritional Sciences and Women’s Health cluster) for REF 2014 was rated as world-leading or internationally excellent. We use this expertise to teach the next generation of health professionals and research scientists. Based across King’s Denmark Hill, Guy’s, St Thomas’ and Waterloo campuses, our academic programme of teaching, research and clinical practice is embedded across six Departments
About the Faculty: https://www.kcl.ac.uk/lsm/index.aspx
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