Research Fellow – AI‑Driven Energy Catalysis

About the role

The AI‑Driven Energy Chemistry group at NTU seeks a dynamic Research Fellow to advance AI‑enabled catalyst design and energy chemistry. You will bridge theoretical chemistry with machine‑learning techniques to deepen understanding of catalytic mechanisms and support sustainable energy solutions.

Key responsibilities

• Conduct machine‑learning research focused on theoretical energy chemistry and catalyst design.
• Develop and run computational simulations (DFT, molecular dynamics) and collaborate with experimental teams.
• Publish findings in peer‑reviewed journals and present at international conferences.
• Provide regular project updates to the principal investigator.
• Assist in the preparation of research proposals and grant applications.

Required profile

• PhD in chemistry, physics, chemical engineering, computer science, or a related discipline.
• Research experience in theoretical catalysis, materials science, AI/ML, or computational modelling.
• Strong publication record and excellent written and spoken communication skills.
• Proficiency in programming for scientific applications.

Required skills

• Machine learning
• Density Functional Theory (DFT)
• Molecular dynamics (MD) simulations
• Scientific programming (e.g., Python)