Research Assistant – AI-Enabled Battery Recycling

About the role

The Energy Research Institute at NTU is seeking a Research Assistant to support an AI‑enabled battery recycling project. You will develop data‑driven models and decision tools that improve the efficiency, yield, and cost‑effectiveness of recycling workflows, contributing to sustainable energy and circular economy goals.

Key responsibilities

• Conduct literature review and problem scoping on battery recycling processes such as hydrometallurgy, pyrometallurgy, and direct recycling.
• Build and curate datasets from experiments, sensors, and public sources, performing data cleaning, labeling, and feature engineering.
• Develop machine‑learning models for process prediction and decision support, including forecasts of metal recovery, impurity levels, energy use, and emissions.
• Design optimization and control methods for resource management (reagent usage, temperature profiles, scheduling, throughput) under safety and quality constraints.
• Support experimental coordination and analysis, translating characterization results into model inputs and evaluation metrics.
• Prepare technical reports, documentation, research manuscripts, and contribute to presentations and project updates.
• Collaborate with the principal investigator, team members, and external partners to meet milestones and deliverables.

Required profile

• Bachelor’s degree in Computer Science, Electrical Engineering, or a related discipline.
• Strong research experience with a demonstrable record of publications.
• Familiarity with machine learning and optimization techniques, including supervised learning, reinforcement learning, or constrained optimization.
• Excellent written and oral communication skills for technical reporting and manuscript preparation.

Required skills

• Machine learning
• Optimization
• Supervised learning
• Reinforcement learning
• Constrained optimization
• Data cleaning
• Feature engineering