At a Glance
- Tasks: Analyse real-world data to support health research and contribute to innovative projects.
- Company: Join the prestigious University of Oxford's Botnar Research Centre.
- Benefits: Gain valuable experience, work in a dynamic environment, and enhance your skills.
- Other info: Full-time, fixed-term role for 2 years with excellent career development opportunities.
- Why this job: Make a real impact on health outcomes while working with cutting-edge data science.
- Qualifications: BA or MSc in Mathematics, Engineering, or related field; programming skills in R required.
The predicted salary is between 30000 - 40000 £ per year.
Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, Botnar Research Centre, Windmill Road, Oxford, OX3 7LD
We have an exciting opportunity for a Research Assistant in Health Data Sciences to join the Pharmaco- and Device epidemiology research group led by Professor Daniel Prieto-Alhambra at the Botnar Research Centre, NDORMS, University of Oxford. The NDORMS Pharmaco- and Device epidemiology research group is involved in a number of national and international studies exploring the conditions of use (adherence, compliance, off and on-label use) of a number of licensed drugs, devices, and vaccines for the prevention and treatment of human disease in 'real world' (routine practice) conditions.
As a Research Assistant in Health Data Sciences you will contribute to the programming of analytical pipelines for the analysis of routinely collected data mapped to the OMOP Common Data Model. You will analyse real world data to address regulatory questions related to the prevalence/incidence of disease, use of medicines/vaccines, and the risks or benefits of medicines/vaccines or devices. You will prepare analytical packages to run a number of pre-specified analyses, contribute to wider project planning, including ideas for new research projects and gather, analyse, and present scientific data from a variety of sources.
You will hold a relevant BA or MSc degree in Mathematics, Engineering, or a related field. Knowledge of medical statistics and experience analysing large datasets, experience in biostatistics and/or health data sciences and experience in the programming of R packages are essential. Experience in propensity scores, overlap weighting, inverse probability weighting and/or similar methods, expertise in pharmaco or vaccine epidemiology and experience of working with electronic medical records/routinely collected data are desirable.
This is a full-time fixed-term appointment for 2 years. The closing date for this position is 12 noon on 10 May 2024. You will be required to upload a CV and supporting statement as part of your online application.
Health Data Sciences Research Assistant: Real-World Data in Oxford employer: University of Oxford
The Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences at the University of Oxford offers a dynamic and collaborative work environment where innovation thrives. As a Research Assistant in Health Data Sciences, you will have access to cutting-edge research projects and the opportunity to contribute to impactful studies that shape healthcare practices. With a strong emphasis on professional development and a supportive culture, this role provides a unique chance to grow your expertise while working alongside leading researchers in a prestigious institution located in the heart of Oxford.
StudySmarter Expert Advice🤫
We think this is how you could land Health Data Sciences Research Assistant: Real-World Data in Oxford
✨Tip Number 1
Network like a pro! Reach out to people in the field of health data sciences, especially those connected to the Nuffield Department. A friendly chat can open doors and give you insights that a job description just can't.
✨Tip Number 2
Show off your skills! If you’ve got experience with R packages or analysing large datasets, don’t just mention it—bring it up in conversations or during interviews. We want to see how you can apply your knowledge to real-world problems.
✨Tip Number 3
Prepare for the interview by brushing up on your understanding of pharmaco-epidemiology. Be ready to discuss how you would tackle regulatory questions using real-world data. It’s all about showing us your thought process!
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who take the initiative to engage directly with us. Don’t miss out on this opportunity!
We think you need these skills to ace Health Data Sciences Research Assistant: Real-World Data in Oxford
Some tips for your application 🫡
Tailor Your CV:Make sure your CV highlights relevant experience and skills that match the job description. We want to see how your background in Mathematics, Engineering, or related fields aligns with the role of a Research Assistant in Health Data Sciences.
Craft a Compelling Supporting Statement:Your supporting statement is your chance to shine! Use it to explain why you're passionate about health data sciences and how your skills in programming and data analysis can contribute to our research group. Be specific about your experiences!
Showcase Your Technical Skills:Don’t forget to mention your experience with R packages and any knowledge of medical statistics. We’re looking for someone who can handle large datasets and has a solid understanding of epidemiological methods, so make sure to highlight these in your application.
Apply Through Our Website:We encourage you to apply directly through our website. It’s the easiest way for us to receive your application and ensures you don’t miss out on any important updates regarding the position. Good luck!
How to prepare for a job interview at University of Oxford
✨Know Your Data
Make sure you brush up on your knowledge of health data sciences and the specific datasets you'll be working with. Familiarise yourself with the OMOP Common Data Model and be ready to discuss how you've used similar models in past projects.
✨Showcase Your Skills
Prepare to demonstrate your programming skills, especially in R. Have examples ready that showcase your experience with analytical pipelines and how you've tackled real-world data analysis in previous roles or projects.
✨Understand the Research Group's Focus
Do your homework on the Pharmaco- and Device epidemiology research group. Understand their current projects and be prepared to discuss how your background and interests align with their work, particularly in relation to drug and vaccine usage.
✨Prepare Thoughtful Questions
Think of insightful questions to ask during the interview. This could include inquiries about ongoing studies, the team’s approach to data analysis, or future research directions. It shows your genuine interest and helps you assess if the role is a good fit for you.
