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Senior Research Associate (Machine-Learning/Signal-Processing) – EUED Programme

Mathematics & Statistics
Salary:   £34,804 to £40,322
Closing Date:   Wednesday 20 January 2021
Interview Date:   To be confirmed
Reference:  A3250

We invite applications for a Senior Research Associate position to work on the development of novel statistical methods within the recently awarded, £1.6M EPSRC “Reducing end use Energy Demand in Commercial Settings Through Digital Innovation” programme, together with several major UK industrial partners.  

This project is an exciting cross-disciplinary collaboration between researchers within the departments of Mathematic & Statistics (Alex Gibberd, Idris Eckley), Computer Science (Adrian Friday) and Environment Sciences (Ally Gormally) at Lancaster University. The focus of the project is on developing and implementing new methods to identify and contextualise patterns in multi-dimensional industrial energy data. Through building an understanding of these patterns the project aims to identify and recommend energy saving strategies for industrial users. Our goal is to create new tools for helping organisations respond to climate change and net zero challenges.  

Lancaster’s internationally recognised Statistics group is one of the largest and strongest Statistics groups in the UK with 25 academic staff, a vibrant community of Post-doctoral researchers and research students. The group sits within the Department of Mathematics and Statistics, one of the UK’s top departments in Mathematics and Statistics, ranked 5th overall in the 2014 Research Excellence Framework and 3rd for the impact of its research 

The department provides an environment which aims to meet the individual needs of each member of staff. We are committed to family-friendly and flexible working policies, and seek to promote a healthy work-life balance. The University is a charter member of Athena SWAN and has held a Bronze award since 2008, in recognition of good employment practice to address gender equality in higher education and research. The Department achieved its own Athena SWAN Bronze award in 2017 and is a registered supporter of the London Mathematical Society’s Good Practice Scheme. 

You should have a PhD in Machine-Learning, Signal-Processing, or a related discipline. You will be experienced in one of more of the following areas: recommender systems, federated/distributed learning, high dimensional statistics, inverse-problems, signal-processing, time-series analysis, or optimisation. Demonstrable ability to produce academic writing of the highest publishable quality is essential. Experience of developing research-level software is desirable but not essential. 

Interested candidates are strongly encouraged to contact Dr. Alex Gibberd ( and/or Professor Adrian Friday ( in advance of making an application. 

You will join us on an indefinite contract however, the role remains contingent on external funding which, at this time is for 36 months. 

Please state in your cover letter your suitability to the role and how you will contribute to the programme.


We welcome applications from people in all diversity groups.

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