AI-Driven HVAC Research Engineer — Edge Energy Optimization

National University of Singapore

Singapore

On-site

SGD 60,000 - 90,000

Full time

5 days ago

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Job summary

National University of Singapore (NUS) at Kent Ridge Campus seeks a Research Engineer (RE) or Research Assistant (RA) to develop AI-driven energy optimization for industrial HVAC systems. The role emphasizes deployment on industrial PCs, data integration from multiple HVAC components, and validation against baseline energy profiles.

The candidate should have a strong HVAC background, familiarity with BMS architectures and protocols, and experience in Python/C++/MATLAB with embedded systems.

Qualifications

Bachelor’s degree with strong academic record and technical HVAC background.
Solid working knowledge of chiller plants, AHUs, CTs, pumps and control logics.
Familiarity with BMS architectures and industrial protocols (BACnet, Modbus, OPC-UA).
Proficiency in Python, C++, or MATLAB; experience with IPCs/edge devices is advantageous.

Responsibilities

Deploy AI-driven HVAC optimization algorithms on IPCs for real-time edge execution.
Build data pipelines from chillers, AHUs, CTs, and pumps using BMS/Modbus/BACnet/OPC-UA.
Integrate and validate control parameters in the BMS to reduce energy use.
Conduct field testing, calibration, and performance validation against baselines.
Assist in documentation, reports, and academic publications.

Skills

Python

C++

MATLAB

Embedded systems

Education

Bachelor’s degree in Electrical Engineering or related

Tools

BACnet

Modbus

OPC-UA

PLC/SCADA

Job description

The candidate should have a strong HVAC background, familiarity with BMS architectures and protocols, and experience in Python/C++/MATLAB with embedded systems.

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