Senior Research Engineer, ARTC

Key Responsibilities

• Develop data-driven energy disaggregation models to estimate machine-, process-, and batch-level energy consumption from aggregated or limited metering data.
• Design and implement energy monitoring, analytics and benchmarking algorithms for energy performance tracking, anomaly detection, and causal analytics related to energy-saving of industrial equipment and manufacturing processes.
• Conduct experiments, model validation, and performance evaluation using industrial datasets.
• Work closely with project partners, engineers, and researchers to translate research outcomes into deployable industrial solutions.

Requirements

• Bachelor’s or Master’s degree in Electrical Engineering, Mechanical Engineering, Computer Science, Data Science, Industrial Engineering, or a related field.
• Strong programming skills in Python, with experience in data analytics, machine learning, and time-series processing.
• Knowledge of energy systems, power consumption analysis, industrial equipment, or manufacturing processes.
• Experience with machine learning techniques for regression, classification, anomaly detection, forecasting, or signal disaggregation.
• Ability to process and analyze large-scale time-series datasets.
• Good problem-solving skills and ability to work independently in applied research and development projects.
• Good written and verbal communication skills.

Preferred Qualifications

• Experience in non-intrusive load monitoring, energy disaggregation, virtual sensing, or industrial energy analytics.
• Experience with deep learning frameworks such as PyTorch or TensorFlow.
• Experience with causal analytics.
• Knowledge of manufacturing systems, additive manufacturing, CNC, heat treatment, pumps, compressors, motors, or other industrial equipment.
• Prior experience in applied R&D projects with industry partners is an advantage.

The above eligibility criteria are not exhaustive. A*STAR may include additional selection criteria based on its prevailing recruitment policies. These policies may be amended from time to time without notice. We regret that only shortlisted candidates will be notified.