About the Role
We have an exciting and unique opportunity for a postdoctoral research assistant to join our Health Data Sciences group investigating the performance of analytical and design methods to minimize bias in pharmaco-epidemiology, comparative safety and effectiveness, and causal inference research. In this role you will analyze OMOP‑mapped real‑world health data assets following pre‑specified protocols and/or using existing analytical pipelines and adapt existing ones to develop new research methodologies for causal inference and real‑world evidence generation.
You will carry out collaborative projects with colleagues in partner institutions, research groups, and key stakeholders as well as collaborate in the preparation of research publications and book chapters. You will also prepare working theories and analyze qualitative and/or quantitative data from a variety of sources, reviewing and refining theories as appropriate.
About You
You will hold a PhD/DPhil (or near completion) in medical statistics, epidemiology, pharmaco‑epidemiology, data science or a related field together with experience in conducting studies using routinely collected health data (RWD). You will have the ability to manage your own academic research and associated activities and prior experience of contributing to publications and/or conference presentations.
You will have demonstrable expertise in the use of R for statistical analysis as well as the flexibility to learn new skills. Experience programming R packages or related analytical code for OMOP‑mapped real‑world data and of designing, conducting and analyzing cohort, case‑control, and similar studies using routinely collected health data are desirable.
Benefits
* An excellent contributory pension scheme
* 38 days annual leave
* A comprehensive range of childcare services
* Family leave schemes
* Cycle loan scheme
* Discounted bus travel and Season Ticket travel loans
* Membership to a variety of social and sports clubs
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