Postdoctoral Researcher in Machine Learning and Power Systems

We are seeking a full-time Postdoctoral Research Assistant in Machine Learning
and Power Systems to join the Energy and Power Group at the Department of
Engineering Science (Osney). The post is funded by the National Energy System
Operator and is fixed-term to 19 December 2025.





Reporting to the Principal Investigator, Professor Malcolm McCulloch, the post
holder will join the Real Time Predictor Innovation project. The main
objective of this project is addressing the critical need to predict accurate
minute-by-minute frequency- aware electricity load prediction aligning with
NESO's unique operational requirements. You will be responsible for



• Developing pre-processing methods (statistical-based method, machine-
learning based method, proposed hybrid method) and comparing them.



• Adapt existing machine-learning methods and develop hybrid ones for high-
resolution load forecasting (based in Python).



• Define different scenarios and clusters based on different features.



• Visualizing the results



• Analyse data and field research towards academic publications.



• Support monitoring and evaluation of the project.



• Produce the required reports associated with the project objectives.



• Tasks as required by the funder and/or in order to publish high-quality
journal papers.





You should possess a relevant Ph.D/D.Phil with post-qualification research
experience, possess specialist knowledge in the analysis and prediction of
time-series data using both traditional and machine learning techniques, plus
is proficient in Python and Machine Learning programmes. There is the
possibility to underfill at Grade 7 (£36,024- £44,263p.a.) if the candidate
holds a relevant PhD/DPhil or is near completion (please note that ‘near
completion’ means that you must have submitted your thesis) and has the
relevant experience.





Informal enquiries may be addressed to Gemma Watson (email:
gemma.watson@eng.ox.ac.uk)





For more information about working at the Department, see



www.eng.ox.ac.uk/about/work-with-us/





Only online applications received before midday on **19 February 2025** can be
considered. You will be required to upload a covering letter/supporting
statement, including a brief statement of research interests (describing how
past experience and future plans fit with the advertised position), CV and the
details of two referees as part of your online application. Interviews are
expected to be held on **26 February 2025.**





The Department holds an Athena Swan Bronze award, highlighting its commitment
to promoting women in Science, Engineering and Technology.