The Role
This is an exciting opportunity for a highly motivated and skilled Research Associate/Assistant in statistics to join the EPSRC funded project PINCODE: Pooling INference and COmbining Distributions Exactly: A Bayesian Approach.
The project aims to address the challenges in pooling inference, by developing and implementing either exact or asymptotically exact Monte Carlo algorithms in collaboration with the Department of Statistics at University of Warwick, Department of Mathematical Sciences at Durham University, and School of Mathematics, Statistics & Physics at Newcastle University.
You will contribute to the development of:
1. An R package for path-space rejection sampling for diffusion processes
2. An R package for Bayesian Fusion pooling inference, such as privacy Bayesian Fusion and constraint Bayesian Fusion
The position is available from 01 March 2026, and is full-time (37 hours per week) on a fixed-term basis until the project end date of 30 June 2028.
For informal enquiries about this vacancy, please contact Dr Murray Pollock ().
For further details about School of Mathematics, Statistics and Physics, please click
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To apply, please complete an online application and upload a CV and a cover letter. Your cover letter is a supporting statement, and you should outline how you meet the essential criteria of the role and evidence this with examples.
Key Accountabilities
3. Contribute to the research programme in the field of Bayesian computational statistics as part of the EPSRC funded ‘PINCODE’ project (EP/X028712/1), under the clear guidance of Prof. Murray Pollock and Prof Hongsheng Dai
4. Work closely with other members of PINCODE, including Prof. L. Aslett (Durham) and Prof G. O. Roberts (Warwick)
5. Participate within the statistical community at Newcastle, including active involvement in seminars and research groups
6. Publish research findings in leading journals
7. Disseminate results widely, including at appropriate national/international conferences, and by making results and software available to applied practitioners
Knowledge, Skills and Experience
8. Evidence of conducting independent, high-quality research
9. High level problem solving and analytical skills
10. Strong programming skills (R or C)
Desirable
11. Experience of using HPC clusters
12. Experience of modern computational statistical methodologies, such as Markov chain Monte Carlo, rejection sampling, sequential Monte Carlo, would be highly desirable
Attributes and Behaviour
13. Ability to work in collaboration with a multi-disciplinary team
14. Strong communication skills, both written and verbal
Qualifications
15. PhD Awarded (for the position as Research Associate) in Mathematics or Statistics or Computer Science
16. or close to completion, having submitted the thesis at the point of starting the position (Research Assistant)
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We are committed to being a fully inclusive university which actively recruits, supports and retains colleagues from all sectors of society. We value diversity as well as celebrate, support and thrive on the contributions of all of our employees and the communities they represent. We are proud to be an equal opportunities employer and encourage applications from individuals who can complement our existing teams, we believe that success is built on having teams whose backgrounds and experiences reflect the diversity of our university and student population.
At Newcastle University we hold a gold award in recognition of our good employment practices for the advancement of gender equality. We also hold a Bronze award in recognition of our work towards tackling race inequality in higher education REC. We are a employer and will offer an interview to disabled applicants who meet the essential criteria for the role as part of the offer and interview scheme.
In addition, we are a member of the Euraxess initiative supporting researchers in Europe.
Requisition ID: 28693