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- Tasks: Curate and analyse health data to support global health projects and create decision-support tools.
- Company: Join the Oxford PHI Lab, a leader in health data sciences and innovation.
- Benefits: Gain valuable experience, collaborate with experts, and contribute to impactful health research.
- Why this job: Make a difference in global health by tackling climate-related health inequities.
- Qualifications: PhD/DPhil in relevant fields and advanced programming skills in R, Python, or SQL.
- Other info: Dynamic research environment with opportunities for professional growth and collaboration.
The predicted salary is between 36000 - 60000 £ per year.
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.
Responsibilities
- Develop analysis plans, ethical protocols, standard operating procedures and similar as required for ongoing and future studies as well as undertake related literature reviews.
- Curate and analyse real‑world health data assets, including data on wider determinants of health e.g. climate.
- Analyse data following pre‑specified analysis plan(s) and/or approved protocols.
- Lead the programming of R/Python packages for the analysis as well as adapt existing and develop new research methodologies and training materials.
- 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.
- 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.
Qualifications
- 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.
- Demonstrable advanced skills in programming in R, Python, SQL, and/or similar languages, together with experience in version control e.g., Git.
- Experience in data visualization and creating digital tools and dashboards using e.g. R Shiny, Power BI, Tableau and/or similar.
- Taught or demonstrated skills in epidemiology study design, analysis, and interpretation and must demonstrate the flexibility to learn new skills and programming languages easily.
Desirable Experience
- 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.
Application Details
The closing date for applications is 12 noon on Monday 16th February 2026. Applications for this vacancy are to be made online. You will be required to upload a CV and supporting statement as part of your online application.
Interview Schedule
Interviews will be held the week commencing 23rd February 2026.
Postdoctoral Research Assistant in Health Data Sciences in Oxford employer: University of Oxford, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences
Contact Detail:
University of Oxford, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Postdoctoral Research Assistant in Health Data Sciences in Oxford
✨Tip Number 1
Network like a pro! Reach out to people in your field, especially those connected to the Oxford PHI Lab. A friendly chat can open doors and give you insider info on what they're really looking for.
✨Tip Number 2
Show off your skills! Prepare a portfolio or a GitHub repository showcasing your R/Python projects, data visualisations, and any dashboards you've created. This will help you stand out during interviews.
✨Tip Number 3
Practice makes perfect! Get ready for technical interviews by brushing up on your programming skills and data analysis techniques. Mock interviews with friends can help you feel more confident.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen. Plus, it shows you're serious about joining the team at StudySmarter and contributing to impactful health data projects.
We think you need these skills to ace Postdoctoral Research Assistant in Health Data Sciences in Oxford
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights the skills and experiences that are most relevant to the role. We want to see how your background in health data sciences aligns with our projects, so don’t hold back on showcasing your programming skills and any relevant research.
Craft a Compelling Supporting Statement: Your supporting statement is your chance to shine! Use it to explain why you’re passionate about this role and how your expertise can contribute to our mission at the Oxford PHI Lab. Be specific about your experience with data analysis and visualisation tools.
Showcase Your Research Experience: Since you'll be involved in drafting scientific manuscripts and reports, make sure to highlight any previous research work you've done. We love seeing examples of your contributions to publications or presentations at conferences, so include those details!
Apply Through Our Website: Don’t forget to submit your application through our website! It’s the easiest way for us to keep track of your application and ensures you’re considered for the role. Plus, it shows you’re serious about joining our team!
How to prepare for a job interview at University of Oxford, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences
✨Know Your Data Inside Out
Make sure you’re well-versed in the health datasets relevant to the role. Brush up on your knowledge of data curation and analysis techniques, especially in R and Python. Being able to discuss specific projects or methodologies you've used will show your expertise.
✨Prepare for Technical Questions
Expect questions about programming and data visualisation tools like R Shiny or Tableau. Practise explaining your past projects and how you approached data analysis. This will help you demonstrate your technical skills and problem-solving abilities.
✨Showcase Your Communication Skills
Since you'll be drafting reports and scientific manuscripts, it’s crucial to convey your ideas clearly. Prepare examples of how you've communicated complex data findings to different audiences. This will highlight your ability to translate technical jargon into understandable insights.
✨Demonstrate Flexibility and Learning Agility
The role requires adapting to new methodologies and programming languages. Be ready to discuss instances where you’ve quickly learned new skills or adapted to changes in a project. This will show that you’re not just a one-trick pony but a versatile team player.
