Research Fellow: Building Energy Systems & AI-Driven Control

Nanyang Technological University; Singapore; On-site; SGD 70,000 - 100,000; Full time

Job summary

NTU's Energy Research Institute @ ERI@N invites applications for a Research Fellow to advance sustainable and advanced building technologies. The role emphasizes research leadership, project coordination, and impactful outputs in energy systems.

The successful candidate will work on building energy/power system control, AI/ML applications, and data-driven modelling, collaborating with engineers and researchers across NTU and partner institutions.

Qualifications

• PhD degree in Mechanical/Electrical Engineering or related field.
• At least 1 year of relevant experience in scientific research / hands-on experience in building energy/power system control & optimisation.
• Familiarity with building energy/power system control & optimisation, BAC, AI & ML applications.
• Good written and oral communication skills.
• Proficiency in power system modelling, advanced control theory (e.g., model-predictive control), data-driven modelling and control methods (e.g., reinforcement learning, transfer learning).
• Proficiency in programming tools and languages, e.g., MATLAB, Python, Modelica, C, Fortran.

Responsibilities

• Support research activities.
• Support research project management.
• Produce research outputs including reports, publications, presentations, etc.
• Coordinate different stakeholders in research projects.
• Support research strategic development and securing funding.
• Support research data management and documentation.

Education

PhD in Mechanical/Electrical Engineering or related field

Tools

MATLAB

Python

Modelica

C

Fortran

Job description

NTU's Energy Research Institute @ ERI@N invites applications for a Research Fellow to advance sustainable and advanced building technologies. The role emphasizes research leadership, project coordination, and impactful outputs in energy systems.

The successful candidate will work on building energy/power system control, AI/ML applications, and data-driven modelling, collaborating with engineers and researchers across NTU and partner institutions.