Senior Research Associate - Detecting Anomalous Structure in Stream Settings (DASS) Programme

Contract type: Open ended

Work hours: 35.0 hours per week

Weeks per year: 52.00

The role

We invite applications for a Senior Post-Doctoral Research Associate positions to join the Statistical Foundations for Detecting Anomalous Structure in Stream Settings (DASS) Programme. The DASS Programme will consider the foundational statistical challenges of identifying anomalous structure in streams within constrained environments, handling the realities of contemporary data streams, and identifying and tracking dependence across streams.

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. The 2 year positions are available at each of the partner universities. 

What will you be doing?

• To contribute to the research project, the primary aim of which is the development of methods and tools for the statistical analysis of data streams and to perform data analyses to illustrate the effectiveness of these techniques.
• To publish in leading statistical journals with other members of the project.
• To attend and contribute to project meetings.
• To attend meetings, workshops and conferences in the UK and abroad, presenting research results and networking.
• To develop code that implements the methods developed to support reproducible research practice.
• To support the Investigators as appropriate in developing the broader collaborative relationship with external partners. 

You should apply if

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 methods or theory 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.

The application process for the four positions is being administered by Lancaster University. Please ensure you state clearly in your cover letter which position, in particular at which universities, you wish to be considered for when applying. These are full-time positions, though we will consider applicants requesting part-time or other flexible working arrangements. We welcome applications from people in all diversity groups.

Additional information

Contract type: Open ended with fixed funding for two years

This advert will close at 23:59 UK time on 10/02/2025

For informational queries, please contact:

Haeran Cho haeran.cho@bristol.ac.uk

Idris Eckley i.eckley@lancaster.ac.uk

Important: applications will only be considered if submitted via the University of Lancaster Jobs Board. Please follow this link to apply: hr-jobs.lancs.ac.uk/Vacancy.aspx?ref=1435-24 

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The University of Bristol aims to be a place where everyone feels able to be themselves and do their best in an inclusive working environment where all colleagues can thrive and reach their full potential. We want to attract, develop, and retain individuals with different experiences, backgrounds and perspectives – particularly people of colour, LGBT+ and disabled people - because diversity of people and ideas remains integral to our excellence as a global civic institution.

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