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Research Assistant in Data Science and Clinical Trials

King's College London - Faculty of Life Sciences & Medicine - Department of Population Health Sciences

Location: London
Salary: £37,332 to £42,099 per annum, including London Weighting Allowance.
Hours: Full Time
Contract Type: Fixed-Term/Contract
Placed On: 22nd April 2024
Closes: 6th May 2024
Job Ref: 088185
 

Job description

We are looking for a Research Assistant to join the Unit for Medical Statistics (UMS) in the School of Life Course & Population Sciences. The postholder will contribute to the work undertaken by existing staff and take day-to-day responsibility for the statistical and database aspects of specific clinical trials and/or other clinical studies and registry projects (epidemiological studies). This will include project planning and protocol development, database 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 graduate with ambitions to work in Data Science and/or clinical trial statistics.

This post will be offered on a fixed-term contract from 01-July-2024 until 30-June-2026.

This is a full time post - 100% full time equivalent / 35 hours per week.

Key responsibilities
  • With senior statistical oversight: to take responsibility for the statistics of several 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.
  • With senior database oversight: The postholder will contribute to the work undertaken by existing staff and will specifically work on standardising operations including back-up procedures and execution, accessing data from existing databases, preparing datasets for statistical analysis and writing code, for example, access code for new databases.
  • Contribute to study reports, publications, proposals and applications to external bodies for funding purposes, as appropriate.
  • To contribute to the UMS statistical consultancy service across King’s, with appropriate training and support, as needed.
  • Identify and solve specific statistical and methodological problems that arise in collected data.
  • Attend and contribute to relevant meetings and conferences.
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. Understanding of database design and management
  5. Knowledge of health research
  6. Committed to equality, diversity and inclusion, actively addressing areas of potential bias 
Desirable Criteria
  1. Experience of analysing clinical research data
  2. Advisory or consultancy experience
  3. 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 five 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, 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 was rated as world-leading or internationally excellent. We use this expertise to teach the next generation of health professionals and research scientists. 

More information: https://www.kcl.ac.uk/slcps

Closing date: 06 May 2024

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