At a Glance
- Tasks: Analyse real-world health data and contribute to innovative research projects.
- Company: Join the prestigious University of Oxford's Botnar Research Centre.
- Benefits: Gain valuable experience in health data sciences with a competitive salary.
- Other info: Full-time role with excellent career development opportunities in a dynamic research environment.
- Why this job: Make a real impact on healthcare by analysing data that influences treatment decisions.
- Qualifications: BA or MSc in Mathematics, Engineering, or related field; programming skills in R required.
The predicted salary is between 30000 - 40000 £ per year.
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.
Research Assistant in Health Data Sciences 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 be part of a leading research group dedicated to impactful studies that shape healthcare practices globally. With access to cutting-edge resources and opportunities for professional development, this role not only enhances your analytical skills but also contributes to meaningful advancements in health data sciences.
StudySmarter Expert Advice🤫
We think this is how you could land Research Assistant in Health Data Sciences
✨Tip Number 1
Network like a pro! Reach out to people in the health data sciences field, especially those connected to the University of Oxford. A friendly chat can open doors and give you insights that a job description just can't.
✨Tip Number 2
Show off your skills! Prepare a mini portfolio showcasing your analytical projects or any relevant work you've done with large datasets. This will help you stand out during interviews and demonstrate your hands-on experience.
✨Tip Number 3
Practice makes perfect! Get comfortable with common interview questions related to health data sciences and programming in R. We recommend doing mock interviews with friends or using online platforms to boost your confidence.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen. Plus, it shows you're genuinely interested in joining our team at StudySmarter. Don’t miss out on this opportunity!
We think you need these skills to ace Research Assistant in Health Data Sciences
Some tips for your application 🫡
Tailor Your CV:Make sure your CV highlights your relevant skills and experiences that align with the Research Assistant role. We want to see how your background in Mathematics, Engineering, or related fields makes you a perfect fit for our team!
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 experience with large datasets and programming in R can contribute to our research group.
Showcase Your Analytical Skills:Since you'll be working with real-world data, it's crucial to demonstrate your analytical prowess. Mention any specific projects where you've used medical statistics or biostatistics to solve problems or draw insights from data.
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!
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 OMOP Common Data Model. Be prepared to discuss how you've previously worked with large datasets and any specific analytical techniques you've used, like propensity scores or inverse probability weighting.
✨Showcase Your Programming Skills
Since programming R packages is essential for this role, be ready to talk about your experience with R. Bring examples of projects where you've developed analytical pipelines or conducted statistical analyses, and if possible, share code snippets or results that demonstrate your skills.
✨Prepare for Scenario Questions
Expect questions that assess your problem-solving abilities in real-world scenarios. Think about how you would approach analysing data for regulatory questions or how you would design a new research project. Practising these scenarios can help you articulate your thought process clearly.
✨Engage with the Research Group's Work
Familiarise yourself with the current studies and projects led by Professor Daniel Prieto-Alhambra's group. Showing genuine interest in their work and being able to discuss it during the interview will demonstrate your enthusiasm and fit for the team.
