School of Electrical and Electronics Engineering, NTU is a is one of the largest and most highly ranked schools in the world with over 3,000 undergraduate students and 2,000 graduate students. It began as one of the three founding schools of Nanyang Technological University, then known as Nanyang Technological Institute. The first intake of 194 students graduated successfully in 1985, marking the first batch of NTU EEE graduates. Today, the School has become one of the world’s largest engineering schools that nurtures competent engineers and researchers. Each year, the School graduates over a thousand students who are ready to take on great ambitions and challenges.
The key objective is to support efforts to nurture engineers and leaders with a broad-based and interdisciplinary education, to pioneer research and innovation for a better future, to contribute to the betterment of society and humanity.
We are looking for a Research Associate to support the development of data-driven solutions for distribution networks with high renewable penetration, contributing to NTU’s mission of advancing sustainable, resilient, and intelligent energy systems. The role will focus on renewable generation forecasting, distribution network modelling and power-flow analysis, building operational databases, and developing/validating AI-enabled state monitoring and state estimation methods for future resilient distribution networks.
Key Responsibilities:
Analyze renewable generation patterns (e.g., PV/wind) in distribution networks and develop short-/medium-term forecasting models for operational planning and uncertainty-aware decision making.
Mathematical modelling of distribution network models, implement power-flow tools and node-/phase-level sensitivity analysis, identify critical buses, quantify the impact of DER variability across locations.
Establish a structured database for data ingestion, cleaning, labeling, and versioning.
Develop AI/ML methods for state monitoring and state estimation.
Validate forecasting, modeling, and state-estimation modules through benchmarking.
Job Requirements:
Master’s degree in electrical engineering or related field
Familiarity with electrical power systems especially in distribution network modelling highly preferred
Experience in optimal power flow and/or state monitoring/statement
Proficient in MATLAB, Python, or similar programming languages
Experience in power systems simulation software packages such as MATLAB/Simulink or OPAL-RT
Excellent verbal and written communication skills in English - essential for data analysis and communication with stakeholders
Able to publish top quality conference/journal papers.
We regret to inform that only shortlisted candidates will be notified.
Hiring Institution: NTU