Direct message the job poster from Transmission Excellence Ltd
Transmission Excellence (TX) is an innovative company that provides simulation software, optimisation software and advisory services to the renewables and power transmission sectors. Our clients include household-name energy companies such as BP and National Grid.
This is a rare opportunity to bridge the gap between power systems and machine learning while working on real-world grid stability challenges. If you’re excited about AI for power systems, we’d love to hear from you.
It is expected that over the next 1-2 years the primary role of the selected candidate will be on an industry-funded research projects that will combine grid simulation and machine learning technologies. This in turn will involve:
·Applying the principles of power system engineering and to the design and simulation of large grid systems.
·Using an electromagnetic transient simulation programme (PSCAD) to create data sets for training, validation and testing,
·Using machine learning software such as Jax and PyTorch.
·Demonstrating your programming expertise using Python (for ML) and C (for embedded model integration)
·Testing software and machine-learning models.
TX will be undertaking this project in collaboration with academic staff at the University of Bristol, who will assist the candidate with the advanced machine learning aspects of the project. The candidate, however, will be responsible for day-to-day implementation and tuning of models.
The selected candidate will be expected to lead on the electrical aspects of the project. Training in PSCAD will be provided, if necessary, but a knowledge of the underlying principles is expected.
A typical day could include:
·Researching & understanding the design of the grid and/or the technical operation of power transmission equipment,
·Discussing with University of Bristol academic staff how best to design and configure machine learning software,
·Writing and documenting machine learning code and/or code to implement the surrogate model within the PSCAD simulation environment,
·Testing the surrogate models developed with machine learning,
·Evaluating test results and consulting with University of Bristol academic staff on how to modify the model or machine learning process to improve results,
At TX we don’t work within the restrictive silos that can be found in larger companies, which makes our work more varied and interesting. The selected candidate must therefore be flexible, and must be willing to help TX respond to immediate client requirements across our businesses and software products.
Requirements:
·A degree in electrical engineering.
·A knowledge of power system modelling techniques.
·Demonstrated ability in computer programming. Experience with machine learning, while not essential, is beneficial.
·2-3 years of experience following completion of first degree. This experience must be in a relevant area such as software development, machine learning or power system analysis. The experience may be acquired in industry or in an academic research role (e.g. a dissertation-only master’s degree or a PhD).
Salary & benefits:
·A £40-50k pa starting salary range (dependent on the extent and relevance of the candidate’s experience).
·Annual salary reviews
·A discretionary bonus of up to 20%
·A 4.5 day week (the office closes at 1pm on Friday)
Workplace Type
On-site. Hybrid work is not available.
Seniority level
* Seniority level
Entry level
Employment type
* Employment type
Full-time
Job function
* Job function
Engineering and Information Technology
* Industries
Research Services
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