At a Glance
- Tasks: Analyse complex clinical data using machine learning to support healthy ageing.
- Company: Nuffield Department of Primary Care Health Sciences, a leader in health research.
- Benefits: Flexible remote work options, competitive salary, and opportunities for professional growth.
- Other info: Collaborative environment with diverse projects and teaching opportunities.
- Why this job: Make a real difference in healthcare by exploring the impact of medications on ageing populations.
- Qualifications: PhD/DPhil in relevant fields and experience in data science and machine learning.
The predicted salary is between 35000 - 45000 £ per year.
Applications are invited for the post of Data Scientist to join the Cardio‑Metabolic‑Renal Research Group in the Nuffield Department of Primary Care Health Sciences, working closely with Professor James Sheppard and Dr Ariel Wang. The post holder will work on the Adverse Drug Events in Ageing Populations (ADDRESS‑AP) project exploring the association between commonly prescribed medications and adverse events such as delirium and falls. The project is being undertaken in collaboration with the AI for Digital Health Research Group, led by Dr Tingting Zhu in the Institute for Biomedical Engineering. The post holder will collaborate closely across these groups and deliver a project using machine learning methods to analyse complex time‑series clinical data relating to treatment prescription and clinical outcomes. The role will also contribute to a diverse portfolio of projects and teaching using routinely collected healthcare datasets with the aim of generating evidence to support healthy ageing in the community.
Responsibilities
- Provide data analysis plans for studies and conduct detailed machine learning analyses
- Advise staff working on related projects
- Develop methodologies for analysis, identify and troubleshoot technical or scientific problems
- Contribute ideas for generating research income
- Lead dissemination activities through the preparation of research publications, book chapters and presentations at conferences or public meetings
Qualifications
- Close to completion of a relevant PhD/DPhil in Mathematics, Statistics, Computing or a related subject
- Relevant experience in data science
- Good knowledge of machine learning algorithms and statistical methods
- Proven competence in programming in Python or similar languages
- Ability to work collaboratively as part of an interdisciplinary team
- Ability to draft manuscripts for publication and present results at conferences
The postholder will be based in the Radcliffe Primary Care, Nuffield Department of Primary Care Health Sciences, Radcliffe Primary Care Building, Woodstock Road, Oxford, OX2 6GG as their normal place of work, but will be able to agree a pattern of regular remote working with their line manager.
Data Scientist in Oxford employer: University of Oxford
The Nuffield Department of Primary Care Health Sciences offers an exceptional work environment for Data Scientists, fostering a culture of collaboration and innovation. Located in the vibrant city of Oxford, employees benefit from access to cutting-edge research projects and opportunities for professional growth, including involvement in interdisciplinary studies that contribute to meaningful advancements in healthcare. With flexible working arrangements and a commitment to supporting healthy ageing, this role provides a unique chance to make a significant impact while enjoying a supportive and dynamic workplace.
StudySmarter Expert Advice🤫
We think this is how you could land Data Scientist in Oxford
✨Tip Number 1
Network like a pro! Reach out to people in the field, especially those connected to the Nuffield Department or similar research groups. 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 portfolio showcasing your data analysis projects, especially any machine learning work. When you get the chance to chat with potential employers, let them see what you can do!
✨Tip Number 3
Practice makes perfect! Get ready for interviews by doing mock sessions with friends or mentors. Focus on explaining your thought process behind data analysis and how you tackle complex problems.
✨Tip Number 4
Apply through our website! We make it easy for you to submit your application directly, and it shows you're serious about joining our team. Plus, you'll be one step closer to working on exciting projects like ADDRESS-AP!
We think you need these skills to ace Data Scientist in Oxford
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the Data Scientist role. Highlight your relevant experience in data science, machine learning, and programming skills. We want to see how your background aligns with the ADDRESS-AP project!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you're passionate about the role and how your skills can contribute to our research group. Don’t forget to mention any collaborative experiences you've had!
Showcase Your Technical Skills:Be specific about your technical skills, especially in Python and machine learning algorithms. We love seeing examples of how you've applied these skills in past projects or research, so don’t hold back!
Apply Through Our Website:We encourage you to apply through our website for a smooth application process. It’s the best way to ensure your application gets into the right hands and shows us you’re serious about joining our team!
How to prepare for a job interview at University of Oxford
✨Know Your Data Science Stuff
Make sure you brush up on your knowledge of machine learning algorithms and statistical methods. Be ready to discuss how you've applied these in past projects, especially in relation to complex time-series data.
✨Show Off Your Collaboration Skills
This role involves working closely with various teams, so be prepared to share examples of how you've successfully collaborated in the past. Highlight any interdisciplinary projects you've been part of and how you contributed to their success.
✨Prepare for Technical Questions
Expect some technical questions related to programming in Python or similar languages. Practise coding problems or data analysis scenarios that might come up during the interview to demonstrate your problem-solving skills.
✨Think About Dissemination
Since the role involves preparing research publications and presentations, think about how you would communicate complex findings to different audiences. Be ready to discuss any past experiences where you've had to present your work effectively.
