Research Associate: AI-Driven Energy Systems & Control

Nanyang Technological University Singapore; Singapore; On-site; SGD 40,000 - 70,000; Full time

Job summary

NTU Energy Research Institute @ NTU (ERI@N) invites applications for a Research Associate to conduct numerical modelling and develop optimal control strategies for energy systems including building energy systems, energy storage, and fire systems.

The role involves data collection from experimental and numerical sources, data organization for model development and validation, and ensuring accuracy and robustness.

Qualifications

• Master’s degree in mechanical/electrical/power engineering or related field.
• At least 1 year of relevant experience in numerical simulations and control.
• Familiarity with building energy system modelling tools (e.g. Matlab, Modelica, TRNSYS, FDS, OpenFOAM).
• Familiarity with experimental methods in energy systems and battery energy storage systems (BESS).
• Familiarity with thermal management methods including heat exchangers, heat sink, PCM, etc.
• Good written and oral communication skills.
• Proficiency in numeric and analytical skills.
• Ability to work independently and develop solutions under strict timelines.

Responsibilities

• Identify credible data sources, standardize data formats, and integrate diverse datasets to enhance reliability of simulations.
• Use AI and machine-learning methods to accelerate numerical simulations.
• Develop optimal control strategies for energy systems.
• Publish high-quality journal papers and conference papers; apply for TD/patents.
• Periodically provide updates on research progress to the PI and team.

Skills

Numerical simulations

Control systems

Data handling

Communication skills

Independent problem solving

Education

Master’s degree in mechanical/electrical/power engineering or related field

Tools

MATLAB

Modelica

TRNSYS

FDS

OpenFOAM

Job description

NTU Energy Research Institute @ NTU (ERI@N) invites applications for a Research Associate to conduct numerical modelling and develop optimal control strategies for energy systems including building energy systems, energy storage, and fire systems.

The role involves data collection from experimental and numerical sources, data organization for model development and validation, and ensuring accuracy and robustness.