AI-Driven Electrocatalyst Discovery for CO2 Reduction

Nanyang Technological University; Singapore; Sur place; SGD 60 000 - 90 000; Plein temps

Résumé du poste

Nanyang Technological University (NTU) in Singapore seeks a Postdoctoral Fellow to advance AI/ML-driven high-throughput, closed-loop experiments for electrocatalytic CO2 reduction. You will integrate automated fabrication and characterization workflows with agentic AI systems to enable autonomous experimentation and data-driven decisions.

The role involves multi-parameter optimization, collaboration with computational researchers, and dissemination of findings through high-quality publications

Qualifications

• PhD in Chemistry, Materials Science and Engineering, Chemical Engineering, or related field.
• Hands-on experience with AI/ML-driven high-throughput experiments.
• Experience with AI-agentic workflows for automation and data analysis.

Responsabilités

• Conduct AI/ML-driven high-throughput, closed-loop experiments for CO2 reduction catalysts.
• Design automated workflows for materials fabrication and characterization.
• Develop multi-parameter optimization strategies for experimental spaces.
• Collaborate with computational researchers to validate predictive models.
• Analyze structure–performance relationships and publish results.
• Present findings at conferences and project meetings.

Connaissances

AI/ML

High-throughput

Data analysis

Autonomous experimentation

Materials science

Electrochemistry

Python

Team collaboration

Formation

PhD in Chemistry

PhD in Materials Science & Engineering

PhD in Chemical Engineering

Outils

Python

TensorFlow

Lab automation

Description du poste

Nanyang Technological University (NTU) in Singapore seeks a Postdoctoral Fellow to advance AI/ML-driven high-throughput, closed-loop experiments for electrocatalytic CO2 reduction. You will integrate automated fabrication and characterization workflows with agentic AI systems to enable autonomous experimentation and data-driven decisions.

The role involves multi-parameter optimization, collaboration with computational researchers, and dissemination of findings through high-quality publications