Senior Research Associate – DASS Programme

RFCSR; Lancaster; On-site; GBP 40,000 - 46,000; Full time

Job summary

Lancaster University invites applications for a Senior Research Associate in the DASS Programme, a major EPSRC-funded initiative uniting Lancaster, Bristol, Warwick and LSE with industry partners. The role encompasses methodological, theoretical and computational research across institutions to deliver advances in statistical science for anomaly detection in streaming data.

This is a full-time postdoctoral position of two years, with flexibility for part-time arrangements; a PhD in Statistics or

Qualifications

• Candidates should hold, or be close to completing, a PhD in Statistics or a closely related discipline.
• Proven ability to develop new statistical theory and methods in areas such as anomaly detection, changepoint analysis, non-stationary time series, high-dimensional statistics, or scalable statistical methodologies.
• Ability to produce high-quality academic writing and collaborate across disciplines.

Responsibilities

• Contribute to methodological, theoretical, and computational research across institutions.
• Develop scalable statistical methods for detecting anomalous structures in streaming data.
• Collaborate with researchers from partner universities and industry to deliver high-impact results.

Skills

Anomalous structure detection

Changepoint analysis

High-dimensional statistics

Time series analysis

Collaborative research

Education

PhD in Statistics or closely related discipline

Job description

General Description –
Lancaster University invites applications for a Senior Research Associate position within the Statistical Foundations for Detecting Anomalous Structure in Stream Settings (DASS) Programme, a major £4 million research initiative funded by the Engineering and Physical Sciences Research Council (EPSRC). This collaborative programme brings together leading researchers from Lancaster University, the University of Bristol, the University of Warwick, and the London School of Economics, alongside a network of industrial and public sector partners.

The DASS Programme focuses on addressing foundational statistical challenges in identifying anomalous structures in modern data streams under constrained environments. It aims to develop robust methodologies capable of handling real-world complexities, including dependence across multiple streams and evolving data environments.

The successful candidate will contribute to methodological, theoretical, and computational research, working collaboratively across institutions to deliver significant advances in statistical science. The role offers an integrated research environment designed to ensure that new statistical methods are scalable, efficient, and applicable across academia, industry, and society.

This is a full-time postdoctoral position with an initial duration of two years, with flexibility for part-time or alternative working arrangements considered. The role provides opportunities to engage in high-impact research, collaborate with leading experts, and contribute to innovative statistical solutions with real-world applications.

Lancaster University offers a supportive and inclusive working environment, with a strong commitment to equality, diversity, and wellbeing. The institution promotes family-friendly policies and encourages applications from individuals of all backgrounds.

Eligibility Criteria –
Applicants should hold, or be close to completing, a PhD in Statistics or a closely related discipline.

Required Expertise/Skills –
Candidates must demonstrate the ability to develop new statistical theory and methods in relevant areas such as anomaly detection, changepoint analysis, non-stationary time series analysis, high-dimensional statistics, statistical-computational trade-offs, or scalable statistical methodologies.

Applicants should also have a proven ability to produce high-quality academic writing suitable for publication, along with strong collaborative and interdisciplinary research skills.

Salary Details –
£39,906 to £46,049 per annum.