At a Glance
- Tasks: Join a dynamic team to develop innovative statistical methods and tackle real-world problems.
- Company: Lancaster University, a leader in mathematical sciences with a collaborative research culture.
- Benefits: Competitive salary, flexible working options, and a supportive work environment.
- Other info: Inclusive workplace that values diversity and promotes well-being for all employees.
- Why this job: Make a significant impact in statistics while collaborating with top researchers across prestigious universities.
- Qualifications: PhD in Statistics or related field, with experience in developing new statistical theories.
The predicted salary is between 39906 - 46049 £ per year.
Location: Bailrigg, Lancaster, UK
Salary: £39,906 to £46,049 (Full-Time/Indefinite with End Date)
Closing Date: Wednesday 10 June 2026
Interview Date: Friday 26 June 2026
Reference: 0264-26
This £4M programme is funded by EPSRC and brings together research groups from the Universities of Lancaster, Bristol, Warwick and the London School of Economics together with a committed group of industrial and public sector partners.
Interaction between the research groups at the universities will be strongly encouraged and resourced; our philosophy is to tackle the methodological, theoretical and computational aspects of these statistical problems together. This integrated approach is essential to achieving the substantive fundamental advances in statistics envisaged, and to ensuring that our new methods are sufficiently robust and efficient to be widely adopted by academics, industry and society more generally.
This programme is led by Idris Eckley (Lancaster University), Haeran Cho (University of Bristol), Paul Fearnhead (Lancaster University), Qiwei Yao (London School of Economics) and Yi Yu (University of Warwick).
This 2-year position is available at Lancaster University. You should have, or be close to completing, a PhD in Statistics or a closely related discipline. Throughout, you should have demonstrated an ability to develop new statistical theory and methods in one of the relevant areas, including but not limited to: anomaly detection; changepoint analysis; non-stationary time series analysis; high dimensional statistics; statistical-computational tradeoffs; scalable statistical methods. You will also have shown a demonstrable ability to produce academic writing of the highest publishable quality.
This is a full-time position, though we will consider applicants requesting part-time or other flexible working arrangements.
Please note: unless specified otherwise in the advert, all advertised roles are UK based.
The University recognises and celebrates good employment practice undertaken to address all inequality in higher education whilst promoting the importance and wellbeing for all our colleagues. We warmly welcome applicants from all sections of the community regardless of their age, religion, gender identity or expression, race, disability or sexual orientation, and are committed to promoting diversity and equality of opportunity.
Senior Research Associate in Statistics – Flexible Working employer: Lancaster University
Lancaster University is an exceptional employer, offering a collaborative and inclusive work environment that fosters innovation in statistical research. With a strong commitment to employee wellbeing, flexible working arrangements, and a focus on professional development, staff are encouraged to thrive both personally and academically. The university's dedication to diversity and equality ensures that all employees feel valued and supported in their contributions to meaningful research.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Research Associate in Statistics – Flexible Working
✨Tip Number 1
Network like a pro! Reach out to your connections in the field of statistics and let them know you're on the lookout for opportunities. You never know who might have the inside scoop on a job or can put in a good word for you.
✨Tip Number 2
Prepare for those interviews! Research the latest trends in statistical methods and be ready to discuss how your skills align with the needs of the programme. Practise common interview questions and think about how you can showcase your unique contributions.
✨Tip Number 3
Don’t just apply anywhere; focus on roles that excite you! Check out our website for positions that match your expertise in anomaly detection or changepoint analysis. Tailor your approach to show why you’re the perfect fit for those specific roles.
✨Tip Number 4
Follow up after interviews! A quick thank-you email can go a long way in keeping you top of mind. Use this opportunity to reiterate your enthusiasm for the role and remind them of how your skills can contribute to their research goals.
We think you need these skills to ace Senior Research Associate in Statistics – Flexible Working
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the Senior Research Associate role. Highlight your PhD and any relevant experience in statistics, especially in areas like anomaly detection or changepoint analysis. We want to see how your skills align with our programme!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you're passionate about this position and how your research aligns with our goals. Be sure to mention any collaborative projects you've been involved in, as we value teamwork.
Showcase Your Writing Skills:Since we’re looking for someone who can produce high-quality academic writing, include examples of your published work or any papers you’ve written. This will give us a taste of your writing style and your ability to communicate complex ideas effectively.
Apply Through Our Website:Don’t forget to apply through our website! It’s the best way to ensure your application gets to us directly. Plus, you’ll find all the details you need about the role and our team there. We can’t wait to hear from you!
How to prepare for a job interview at Lancaster University
✨Know Your Stats
Brush up on your statistical theories and methods relevant to the job. Be ready to discuss your PhD work and how it relates to anomaly detection, changepoint analysis, or any other key areas mentioned in the job description.
✨Showcase Collaboration Skills
Since the role involves working with various research groups, prepare examples of past collaborations. Highlight how you’ve successfully worked in teams to tackle complex problems, as this will demonstrate your ability to fit into their integrated approach.
✨Prepare for Technical Questions
Expect technical questions that assess your understanding of statistical-computational trade-offs and scalable methods. Practise explaining complex concepts in simple terms, as this shows not only your knowledge but also your communication skills.
✨Ask Insightful Questions
Prepare thoughtful questions about the programme and its goals. Inquire about the specific challenges they face in statistical methods and how you can contribute. This shows your genuine interest and helps you gauge if the role is right for you.
