Research Engineer, Optimal Energy Management of Multi-Microgrids job with NATIONAL UNIVERSITY OF SINGAPORE


job description

We are looking for a research engineer to work on optimizing the energy efficiency of several networked micro-grids.

The position mainly covers the following tasks.

  • Take responsibility for the concept, design, analysis, modeling and simulation of the large-scale distributed power grid system.
  • Be involved in the development of algorithms to improve the performance of the large-scale distributed power grid system, in particular with the distributed optimization algorithms and reinforcement learning architecture.
  • Work closely with a micro-grid simulation team to verify the proposed algorithm and help test the simulation software as appropriate.
  • Developed the UI interface of the optimization software to better demonstrate its function to the industry.
  • Ensure that the design of the system conforms to existing certification standards.
  • Provide support to a team of engineers in solving multidisciplinary problems, including preparing documentation and presenting analysis / test results to peers and clients.
  • Conduct high quality research, come up with research ideas and be an active member of the department.


The candidate should have interdisciplinary experience in related fields such as distributed optimization, control theory, AI-based data-driven optimization like reinforcement learning and fundamental knowledge in power systems.

  • Hold a bachelor’s degree in engineering and / or a related discipline
  • Evidence of published research with a strong publication record in high quality journals.
  • Demonstrated experience in technical programming languages ​​such as MATLAB, Python or Julia.
  • Extensive knowledge and hands-on programming experience with deep learning frameworks and packages eg PyTorch, TensorFlow or Flux.
  • In-depth knowledge of distributed optimization architectures such as ADMM and in-depth knowledge of evolutionary optimization algorithms such as genetic algorithm.
  • Knowledge of distributed reinforcement learning algorithms such as MADDPG is highly preferred.
  • Basic knowledge of control theory and electrical systems.
  • Has technical proposal writing and presentation skills.
  • Able to plan and organize well and meet deadlines.
  • Able to do research in a multidisciplinary team.
  • Open to CDD

More information

Site: Kent Ridge Campus
Organization: Engineering
department : Electrical and computer engineering
Eligible for employee recommendation: No
Job Application ID: 10793


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