Botnar Research Centre, Windmill Road, Oxford, OX3 7LD 184138 Postdoctoral Research Assistant in Health Data Sciences Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences (NDORMS) Grade 7: £39,424 per annum. This is a full time (part time may be considered - minimum 80% FTE), fixed term position for 12 months or until 31st August 2027. The Oxford PHI Lab is seeking a highly motivated data scientist to support our projects on curation and modelling of harmonised health datasets and co-creating publicly available decision-support dashboards and tools to enhance mapping, monitoring, and prediction of global health challenges including mitigating climate-exacerbated global health inequities. This includes a new project funded by the Gates Foundation on real-world data for women’s health. In this role, you will develop analysis plans, ethical protocols, standard operating procedures and similar as required for ongoing and future studies as well as undertake related literature reviews. You will curate and analyse real world health data assets, including data on wider determinants of health e.g. climate. As well as analyse data following pre-specified analysis plan/s and/or approved protocols. In this position you will lead the programming of R/Python packages for the analysis as well as adapt existing and develop new research methodologies and training materials. You will report research findings in the form of conference abstracts at national and international conferences and collaborate in the preparation of research publications, and book chapters. Additionally, you will lead and/or support the drafting of scientific manuscripts, reports to funders and other materials for other audiences based on the results from research studies. You must hold a PhD/DPhil (or be near completion) in epidemiology, public health, applied/medical statistics, bio/medical engineering, health data sciences, health informatics, computer science, clinical artificial intelligence, environmental epidemiology, climate data sciences, remote sensing, earth observation, public health geography, or a similar field. You will have demonstrable advanced skills in programming in R, Python, SQL, and/or similar languages, together with experience in version control e.g., Git. You will be able to demonstrate experience in data visualization and creating digital tools and dashboard using e.g. R Shiny, Power BI, Tableau and/or similar. You must have taught or demonstrated skills in epidemiology study design, analysis, and interpretation and must demonstrate the flexibility to learn new skills and programming languages easily. Experience in cleaning and analysing health data e.g., electronic health records, and/or satellite-derived data analysis products and GIS data as well as experience in medical large language models and foundation models e.g., through HuggingFace are desirable.