At a Glance
- Tasks: Conduct groundbreaking research in computational complexity and mentor junior researchers.
- Company: Join the prestigious University of Oxford, a leader in global research and innovation.
- Benefits: Enjoy 38 days of annual leave, a great pension scheme, and flexible working options.
- Other info: Be part of a diverse team committed to tackling global challenges.
- Why this job: Make a real impact on complex problems while advancing your academic career.
- Qualifications: PhD in a relevant field and strong research skills required.
The predicted salary is between 36000 - 60000 £ per year.
We are seeking a highly motivated Postdoctoral Research Associate (up to 4 posts) to join our team. The post holder will become a member of a research group with responsibility for carrying out research on the European Research Council Project METACOMP on “Meta-Complexity: A Unified Approach to the Complexity of Proofs and Computation”, with Rahul Santhanam as Principal Investigator. The post holder will be reporting to the Principal Investigator and provide guidance to junior members of the group, such as PhD students and interns. This role is offered with full‑time hours, on a fixed‑term basis for 2 years.
The University of Oxford is a stimulating work environment, which enjoys an international reputation as a world‑class centre of excellence. Our research plays a key role in tackling many global challenges, from reducing our carbon emissions to developing vaccines during a pandemic. The Department of Computer Science at Oxford is renowned for pioneering research and teaching across diverse fields, consistently ranking among the best in the world. Our commitment to innovation drives us to tackle complex technological and societal challenges.
As an employer, we genuinely care about our employees’ wellbeing, reflected in the range of benefits that we offer including:
- Excellent contributory pension scheme
- 38 days annual leave (including public holidays)
- Family leave schemes
- Cycle loan scheme and discounted public transport
The successful candidate will work onsite in the Department of Computer Science buildings in central Oxford, however remote and flexible working can be considered.
Committed to equality and valuing diversity.
You will be required to upload a supporting statement and an up‑to‑date CV as part of your online application. Your supporting statement must clearly demonstrate how you meet each of the essential selection criteria listed in the job description. Applications that do not include a supporting statement or CV, or fail to address the criteria in sufficient detail, will not be considered. While we recognise the value of AI tools in assisting with application preparation, submissions that are clearly AI‑generated without personalisation or insight will be rejected. It is crucial that your application reflects your own experiences and understanding of the role. The closing date for applications is midday on 13th March 2026. Interviews are expected to be held in March.
Postdoctoral Research Associate in Computational Complexity in Oxford employer: University of Oxford, Dept of Computer Science
The University of Oxford is an exceptional employer, offering a vibrant and intellectually stimulating environment that fosters innovation and collaboration. With a strong commitment to employee wellbeing, we provide generous benefits such as a contributory pension scheme, 38 days of annual leave, and opportunities for professional growth within a world-renowned research community. Working in the heart of Oxford, you will be part of a diverse team dedicated to addressing global challenges through cutting-edge research.
Contact Details:
University of Oxford, Dept of Computer Science Recruitment Team
StudySmarter Expert Advice🤫
We think this is how you could land Postdoctoral Research Associate in Computational Complexity in Oxford
✨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like University of Oxford, Dept of Computer Science!
✨Show Off Your Projects
Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Postdoctoral Research Associate in Computational Complexity at University of Oxford, Dept of Computer Science.
✨Leverage Professional Networks
Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like University of Oxford, Dept of Computer Science.
✨Apply Directly through Our Website
When you find a suitable opening like Postdoctoral Research Associate in Computational Complexity at University of Oxford, Dept of Computer Science, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!
We think you need these skills to ace Postdoctoral Research Associate in Computational Complexity in Oxford
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at University of Oxford, Dept of Computer Science, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at University of Oxford, Dept of Computer Science. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at University of Oxford, Dept of Computer Science
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at University of Oxford, Dept of Computer Science!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
