Researcher Power Systems
Invenia Labs is looking for a researcher with a power systems specialisation who has a deep knowledge of modern power systems, their operations, control, and economics.
You will work closely with our Machine Learning Research Scientists and Research Engineers and use their domain specific knowledge and insights to improve our understanding of all aspects of power systems, and to improve their efficiency. You will also have the opportunity to be active in the wider research community by partnering with universities, publishing research papers, and attending conferences.
- Collaborate with other research scientists and share domain specific knowledge to guide research and modelling choices.
- Present research clearly and concisely, both verbally and in writing, for internal and external use as appropriate.
- Keep up to date with publications from Independent System Operators, regulators, and research on power system operations, control, and economics.
- Collaborate with and maintain external relationships within electricity industry and research labs.
- Attend conferences and publish research papers.
- MSc/PhD in Power Engineering, Electrical Engineering, or equivalent experience in power system operations, control, and economics.
- Expertise in one or more of the following areas: theory and implementation of large scale power grid simulations and optimisation, and forecasting of load, generation, and renewables.
- Deep understanding of the driving factors of non-stationary day-ahead and real-time power system planning and operations, and their interactions.
- Knowledge of the operations of power grids, RTOs, ISOs in North America and globally.
- Experience with statistical data modeling, numerical methods, and optimization techniques.
- Good coding skills and knowledge of scientific computing concepts and methods.
Invenia Labs uses machine learning to optimise the electricity grid, ensure demands are met at least-possible prices and minimum pollution. Our work helps to reduce emissions and pollution, improve the reliability of the grid and increase economic efficiency.