Postdoctoral Research Associate in Statistical Computing

University of Edinburgh; City of Edinburgh; On-site; GBP 41,000 - 49,000; Full time

Job summary

A leading research university in Scotland seeks a postdoctoral researcher in statistical computing methods. In this role, you will develop advanced statistical modeling techniques and contribute to a collaborative project aimed at creating a state-of-the-art Python package. Applicants should hold a PhD in a related field and possess a strong publication record. The role offers competitive compensation and an exciting working environment.

Benefits

Generous holiday entitlement

Competitive pension schemes

Staff discounts

Family-friendly initiatives

Qualifications

• Proven statistical publication track record, with a sound methods component.
• Good knowledge of modern statistical regression, particularly smoothing and mixed models.
• Strong background in Bayesian and frequentist statistical methods.

Responsibilities

• Develop scalable and stable smooth statistical modelling methods.
• Implementation of methods in a state-of-the-art python package.
• Work collaboratively with industrial partners and academic staff.

Skills

Statistical publication track record

Strong mathematical skills

Numerical skills

Software engineering skills

Knowledge of Bayesian methods

Knowledge of frequentist methods

Education

PhD in statistical computing methods or closely related field

Tools

Python

Job description

Overview

Grade UE07 £41,064 - £48,822 per annum
CSE / School of Mathematics
Full time: 35 hours per week
Fixed term: from 1st January 2026 until 31st December 2029

The Opportunity

We are looking for a postdoctoral researcher in statistical computing methods, to work on the next generation of scalable and stable smooth statistical modelling methods, and their implementation in a state of the art python package. This 4 year project is collaborative with industrial partners and Simon Wood (the author of R package mgcv for smooth regression modelling).

The researcher will work with Simon Wood, industrial partners and students on developing statistical computing methods for general smooth regression models in large data - large model settings, and on innovative smoothing parameter and uncertainty quantification methods for general smooth models that approach O(np) computational complexity. As well as conventional academic methods development, a second strand of the work aims to produce the state of the art native python package for general smooth regression modelling, improving on mgcv, incorporating the new methods and providing seamless integration with industrial python based data analysis workflows.

Your skills and attributes for success

• A PhD in statistical computing methods or closely related field.
• Proven statistical publication track record, with a sound methods component.
• Strong mathematical, numerical and software engineering skills.
• Good knowledge of modern statistical regression, particularly smoothing and mixed models.
• A strong background in Bayesian and frequentist statistical methods.

Click to view a copy of the full job description.

Applicants should upload a CV and a brief research statement (max 2 pages) when applying for the post. For informal enquiries please contact Professor Simon Wood, [e-mail].

What you can expect

As a valued member of our team you can expect:

To play a key part in producing methods that get used and make a difference to how data are analysed in practice, as part of a collaborative team based in the statistics group in the School of Mathematics. The statistics group (formally part of the data and decisions theme, with operational research) comprises 22 members of academic plus students and postdocs staff. With interests in statistical computing, AI and ML, medical and environmental statistics, Bayesian computing methods, high dimensional data, extremes, finance, statistics in the law, causality and beyond the group has an active and lively research culture underpinned by the Centre for Statistics.

Edinburgh is a fantastic place to live, with a thriving cultural scene epitomised by its huge month long arts festival every August; excellent connections to the rest of the UK and Europe (4.5 hours direct to the Eurostar terminal); and close proximity to the hills, lochs and coastline that make Scotland so appealing to anyone who enjoys the outdoors.

You will benefit from comprehensive Staff Benefits, such as a generous holiday entitlement, competitive pension schemes, staff discounts, and family-friendly initiatives. Check out the full list on our staff benefits page and use our reward calculator to discover the total value of your pay and benefits

Equality and commitment

Championing equality, diversity and inclusion
The University of Edinburgh holds a Silver Athena SWAN award in recognition of our commitment to advance gender equality in higher education. We are members of the Race Equality Charter and we are also Stonewall Scotland Diversity Champions, actively promoting LGBT equality.

Prior to any employment commencing with the University you will be required to evidence your right to work in the UK. Further information is available on our right to work webpages.

The University may be able to sponsor the employment of international workers in this role. This will depend on a number of factors specific to the successful applicant.

Key dates to note

The closing date for applications is 2 October 2025.

Unless stated otherwise the closing time for applications is 11:59pm GMT. If you are applying outside the UK the closing time on our adverts automatically adjusts to your browsers local time zone.

Interviews will be held week commencing 20th October.

About Us

As a world-leading research-intensive University, we are here to address tomorrow's greatest challenges. Between now and 2030 we will do that with a values-led approach to teaching, research and innovation, and through the strength of our relationships, both locally and globally.

About the Team

The School of Mathematics

The University of Edinburgh's School of Mathematics is one of the world's leading mathematical sciences departments, home to world-class researchers and to an innovative educational environment for both undergraduates and postgraduates. We are proud to have a highly international faculty and students from around the world. As a School we value both the breadth and depth of our research and teaching.

We have around 110 permanent faculty and around 45 research fellows and research associates, who cover a broad range of research topics in pure and applied mathematics, operational research and statistics. The School has an enviable record of attracting prestigious fellowships and currently hosts, for instance, 6 ERC grant holders and 7 Royal Society University Research and Dorothy Hodgkin Fellows. In the 2023 Shanghai Global Ranking of Academic Subjects we are ranked 18th among the world's best Mathematics departments. Together with the Departments of Mathematics and Actuarial Mathematics & Statistics at Heriot-Watt University, we form the Maxwell Institute; our joint submission to REF2021 was ranked 3rd in the UK for Mathematical Sciences by research power, based on the quality and breadth of our combined research.

The School delivers a world-leading educational experience for its students and is constantly exploring new evidence-based ideas in mathematical education in order to provide a stimulating learning environment. There are excellent possibilities for imaginative curriculum development, including online activities, and course design and delivery. The School teaches pure and applied Mathematics, operational research and statistics. We have approximately 1000 undergraduate students, around 210 MSc students, and our Graduate School has close to 160 PhD students.

Edinburgh is home to the International Centre for Mathematical Sciences, one of the UK's two major conference centres in the mathematical sciences and operated jointly by the University with Heriot-Watt University. Over the past 30 years the centre has established a superb reputation for hosting workshops at the highest scientific level on all mathematical topics, attracting many of the best mathematicians in the world to the UK.

The School is located in the James Clerk Maxwell Building which is situated on the King\'s Buildings campus, approximately 3 kilometres south of the city centre.

Further information about the School, our research and our teaching is available on the School of Mathematics Website (https://www.maths.ed.ac.uk)