AI-Driven Postdoc: Autonomous CO₂ Reduction Catalysis

Aimlroles; Singapore; On-site; SGD 60,000 - 90,000; Full time

Job summary

NTU is seeking a Postdoctoral Fellow in the School of Materials Science and Engineering to lead AI/ML-driven high-throughput, closed-loop experimentation for CO2-reduction electrocatalysts. The role involves integrating automated fabrication and characterization workflows with autonomous AI agents, and collaborating with computational and electrochemical teams to validate models.

You will optimize multi-parameter experimental spaces, study structure–performance relationships, and contribute to

Qualifications

• PhD in Chemistry, Materials Science and Engineering, Chemical Engineering, or closely related field.
• Experience designing AI/ML-driven high-throughput experiments.
• Experience with AI-agentic workflows for automation and data analysis.
• Experience in multi-parameter optimization and structure–performance analysis.
• Strong publication record and ability to independently plan and manage research activities.

Responsibilities

• Conduct AI/ML-driven high-throughput, closed-loop experimentation to accelerate discovery, evaluation, and optimization of electrocatalytic materials for CO2 reduction.
• Design and develop automated workflows for materials fabrication and characterization, integrating AI agents to enable autonomous experimentation and decision-making.
• Develop and implement multi-parameter optimization strategies to explore complex experimental process spaces, including in-situ catalyst regeneration.
• Collaborate with computational researchers to evaluate and validate predictive models, integrating experimental feedback to improve model performance.
• Analyze and interpret experimental results, investigate structure–performance relationships, and identify key factors influencing electrocatalytic performance.
• Prepare and publish high-quality research articles in peer-reviewed scientific journals.
• Communicate research findings through presentations at scientific conferences, project meetings, and programme reviews.

Skills

AI/ML in experiments

High-throughput experimentation

Autonomous experimentation

Multi-parameter optimization

Data-driven discovery

Education

PhD in Chemistry, Materials Science & Engineering, Chemical Engineering

Tools

Automation workflows

Job description

NTU is seeking a Postdoctoral Fellow in the School of Materials Science and Engineering to lead AI/ML-driven high-throughput, closed-loop experimentation for CO2-reduction electrocatalysts. The role involves integrating automated fabrication and characterization workflows with autonomous AI agents, and collaborating with computational and electrochemical teams to validate models.

You will optimize multi-parameter experimental spaces, study structure–performance relationships, and contribute to