At a Glance
- Tasks: Investigate methods to minimise bias in health data research and causal inference.
- Company: Join the prestigious University of Oxford's Health Data Sciences group.
- Benefits: Competitive salary, excellent pension scheme, and 38 days annual leave.
- Other info: Be part of a leading institution with a focus on innovative research.
- Why this job: Make a real impact in health research while advancing your career.
- Qualifications: PhD/DPhil in a relevant field and expertise in R for statistical analysis.
The predicted salary is between 39424 - 43984 € per year.
The University of Oxford is seeking a postdoctoral research assistant in the Health Data Sciences group. This role focuses on investigating methods to minimize bias in pharmaco-epidemiology and causal inference research.
Applicants should have a PhD/DPhil in a relevant field and expertise in R for statistical analysis.
The position offers a salary range of £39,424-£43,984 per annum and includes an excellent pension scheme, 38 days annual leave, and other benefits.
Postdoctoral Health Data Scientist — Causal Inference & RWD employer: University of Oxford
The University of Oxford is an exceptional employer, offering a vibrant work culture that fosters innovation and collaboration in the Health Data Sciences group. With generous benefits including 38 days of annual leave and a robust pension scheme, employees are encouraged to pursue their professional growth while contributing to impactful research in pharmaco-epidemiology. Located in one of the world's leading academic institutions, this role provides unique opportunities to engage with cutting-edge methodologies and make meaningful contributions to public health.
StudySmarter Expert Advice🤫
We think this is how you could land Postdoctoral Health Data Scientist — Causal Inference & RWD
✨Tip Number 1
Network like a pro! Reach out to your connections in the health data science field, especially those at the University of Oxford. A friendly chat can sometimes lead to opportunities that aren’t even advertised.
✨Tip Number 2
Show off your skills! Prepare a portfolio showcasing your expertise in R and any relevant projects you've worked on. This will help you stand out during interviews and demonstrate your practical knowledge.
✨Tip Number 3
Practice makes perfect! Conduct mock interviews with friends or mentors to refine your answers, especially around causal inference and pharmaco-epidemiology. The more comfortable you are, the better you'll perform.
✨Tip Number 4
Don’t forget to apply through our website! We’ve got loads of resources to help you land that dream job, so make sure you take advantage of everything we offer to boost your application.
We think you need these skills to ace Postdoctoral Health Data Scientist — Causal Inference & RWD
Some tips for your application 🫡
Tailor Your CV:Make sure your CV highlights your relevant experience in health data sciences and causal inference. We want to see how your skills align with the role, so don’t be shy about showcasing your expertise in R and any related projects you've worked on.
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you're passionate about pharmaco-epidemiology and how your background makes you a perfect fit for our team. Keep it engaging and personal – we love to see your personality come through!
Showcase Your Research Skills:Since this role involves minimising bias in research, make sure to highlight any relevant research methodologies you've used in the past. We’re keen to see how you approach complex problems and your ability to apply statistical analysis effectively.
Apply Through Our Website:We encourage you to submit your application through our website. It’s the easiest way for us to keep track of your application and ensures you don’t miss out on any important updates. Plus, it shows you’re serious about joining our team!
How to prepare for a job interview at University of Oxford
✨Know Your Stuff
Make sure you brush up on your knowledge of pharmaco-epidemiology and causal inference. Be ready to discuss specific methods you've used in your research and how they relate to minimising bias. This shows you're not just familiar with the theory but can apply it practically.
✨Show Off Your R Skills
Since expertise in R is crucial for this role, prepare to demonstrate your proficiency. You might be asked to solve a problem or explain how you've used R for statistical analysis in your previous work. Bring examples of your code or projects to discuss.
✨Ask Insightful Questions
Prepare thoughtful questions about the Health Data Sciences group and their current projects. This not only shows your interest in the role but also helps you gauge if the team and environment are the right fit for you.
✨Highlight Your Collaboration Experience
Research often involves teamwork, so be ready to share examples of how you've collaborated with others in your field. Discuss any interdisciplinary projects you've been part of, as this will demonstrate your ability to work well in a diverse team.
