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.
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