At a Glance
- Tasks: Support analysis and management of health data studies using real-world data.
- Company: Join the prestigious University of Oxford's research team in epidemiology.
- Benefits: Gain valuable experience, work with experts, and contribute to impactful research.
- Other info: Full-time, fixed-term role for 2 years with opportunities for career growth.
- Why this job: Make a difference in public health while developing your skills in a dynamic environment.
- Qualifications: Post-graduate degree in Epidemiology or related field; experience in biostatistics and R programming.
The predicted salary is between 30000 - 40000 £ per year.
We have an exciting opportunity for a Research Assistant in Epidemiology and 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 Epidemiology and Health Data Sciences you will support the analysis and management for studies on our portfolio using routinely collected data mapped to the OMOP Common Data Model. You will contribute to the development of study documentation for our studies, you will use R packages to run a number of pre-specified analyses and you will conduct and support research activities based on your relevant expertise area.
You will contribute to publications, scientific reports and journal articles as well as the presentation of data/papers at conferences and other scientific meetings.
You will hold a relevant post-graduate degree in Epidemiology or a related field together with experience in biostatistics and/or health data sciences. Experience in programming statistical analyses, preferably in R and experience in writing scientific documents, e.g. study reports, manuscripts are essential. As are ability to work within multi-disciplinary teams and independently, good communication skills and excellent team working skills.
Experience in the analysis or interpretation of OMOP-mapped data, experience in working with electronic medical records/routinely collected/real world data and experience in generating phenotypes 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.
Real-World Data Research Assistant – Epidemiology 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 in health data sciences thrives. As a Research Assistant in Epidemiology, you will benefit from access to cutting-edge research facilities, opportunities for professional development, and the chance to contribute to impactful studies that shape healthcare practices globally. Join a team that values diversity, fosters growth, and is dedicated to advancing knowledge in real-world data applications.
StudySmarter Expert Advice🤫
We think this is how you could land Real-World Data Research Assistant – Epidemiology in Oxford
✨Tip Number 1
Network like a pro! Reach out to people in the field of epidemiology and health data sciences. Attend conferences, webinars, or local meet-ups to connect with professionals who can give you insights or even refer you to opportunities.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your work with R packages and any relevant projects you've completed. This will help you stand out when chatting with potential employers or during interviews.
✨Tip Number 3
Prepare for interviews by brushing up on common questions related to epidemiology and health data sciences. Be ready to discuss your experience with OMOP-mapped data and how you've contributed to research projects in the past.
✨Tip Number 4
Don’t forget to apply through our website! We’ve got loads of opportunities that might be perfect for you. Plus, it’s a great way to ensure your application gets seen by the right people.
We think you need these skills to ace Real-World Data Research Assistant – Epidemiology in Oxford
Some tips for your application 🫡
Tailor Your CV:Make sure your CV highlights your relevant experience in epidemiology and health data sciences. We want to see how your skills align with the role, so don’t be shy about showcasing your biostatistics and programming expertise!
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 background makes you a perfect fit for our research group. Be specific about your experience with R and any relevant projects you've worked on.
Show Off Your Team Spirit:We love team players! In your application, mention any experiences where you’ve successfully collaborated with others. Highlighting your ability to work within multi-disciplinary teams will definitely catch our eye.
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 ensure it gets the attention it deserves. Plus, it shows you’re serious about joining our team!
How to prepare for a job interview at University of Oxford
✨Know Your Data Inside Out
Make sure you’re familiar with the OMOP Common Data Model and how it relates to real-world data. Brush up on your experience with electronic medical records and be ready to discuss specific examples of how you've used data in your previous roles.
✨Show Off Your R Skills
Since programming statistical analyses in R is essential for this role, prepare to demonstrate your proficiency. Bring along examples of R packages you've used and be ready to explain your approach to running analyses during the interview.
✨Communicate Clearly
Good communication skills are a must, so practice explaining complex epidemiological concepts in simple terms. Think about how you would present your findings to a non-technical audience, as this will show your ability to work within multi-disciplinary teams.
✨Prepare for Teamwork Questions
Expect questions about your experience working in teams. Have a few anecdotes ready that highlight your collaboration skills, especially in multi-disciplinary settings. This will help demonstrate that you can thrive both independently and as part of a team.
