Research Engineer, Optimal Energy Management of Multi-Microgrids

25 Jan 2022
End of advertisement period
20 Feb 2022
Contract Type
Fixed Term
Full Time

Job Description

We are looking for a Research Engineer to work on energy efficiency optimization for multiple networked microgrids. 

The job mainly covers the following tasks.

  • Take responsibility for the concept, design, analysis, modeling, and simulation of the distributed large-scale power grid system.
  • Be involved in the algorithm development to improve the performance of the distributed large-scale power grid system, especially with the distributed optimization algorithms and reinforcement learning architecture.
  • Collaborate closely with a microgrid simulation team to verify the proposed algorithm and assist with testing the simulation software when applicable.
  • Develop the UI interface of the optimization software to better demonstrate its function toward the industry.
  • Ensure system design complies with existing standards for certification.
  • Provide support to a team of engineers in solving multi-disciplinary problems, including preparing documentation and presenting results of analyses/testing to peers and customers.
  • Conduct high-quality research, propose his/her research ideas, and be an active member of the department.


The candidate is expected to 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.

  • Possess a Bachelor Degree in Engineering and/or related discipline
  • Evidence of published research with a strong publication record in high quality journals.
  • Proven experience with technical programming languages like MATLAB, Python, or Julia.
  • Profound knowledge and hands-on programming experience with deep learning frameworks and packages, e.g., PyTorch, TensorFlow, or Flux.
  • Profound knowledge in distributed optimization architectures such as ADMM and profound knowledge in evolutionary optimization algorithms such as genetic algorithm.
  • Knowledge in distributed reinforcement learning algorithms such as MADDPG is highly preferred.
  • Basic knowledge in control theory and power systems.
  • Has technical proposal writing and presentation skills.
  • Able to plan and organize well and adhere to deadlines.
  • Able to do research in a multi-disciplinary team.
  • Open to fixed term contract

More Information

Location: Kent Ridge Campus
Organization: Engineering
Department : Electrical And Computer Engineering
Employee Referral Eligible: No
Job requisition ID : 10793

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