AI-Driven Catalysis Research Assistant

NATIONAL UNIVERSITY OF SINGAPORE; Singapore; On-site; SGD 65,000 - 95,000; Full time

Job summary

The National University of Singapore invites applications for a research position working with Assistant Professor Ou Pengfei on computational and data-driven catalyst modelling under an MOE AcRF Tier 1 project. The work aims to integrate first-principles calculations with machine-learning approaches to understand nitrogen activation on catalyst surfaces.

The successful candidate will perform DFT calculations, build and curate computational datasets, develop descriptors, and apply interpretable

Qualifications

• Bachelor's degree or higher in Chemistry, Materials Science, Chemical Engineering, Physics, or related field.
• Experience in computational chemistry, materials modelling, or data-driven materials research is advantageous.

Responsibilities

• Perform DFT calculations to investigate adsorption structures, reaction energetics, and elementary pathways for nitrogen-containing intermediates on catalyst surfaces.
• Construct, curate, and analyse computational datasets of catalyst structures, adsorption energies, and reaction energetics.
• Develop physically meaningful descriptors and apply machine-learning methods to identify structure-property and structure-reactivity relationships.
• Apply interpretable machine-learning approaches (e.g., symbolic regression, feature attribution) to identify key factors governing catalytic performance.
• Screen catalyst candidates using computational models and propose promising compositions or active-site environments for further study.
• Analyse computational results, prepare figures and reports, and contribute to publications and presentations.
• Collaborate with group members and experimental partners to validate predictions and refine catalyst-design strategies.

Skills

DFT knowledge

Atomistic modelling

Python

Machine learning

Interpretable ML

Data analysis

Scientific writing

Education

Bachelor's or higher in Chemistry / Materials Science / Physics

Tools

VASP

SHAP

SISSO

Python tooling

Job description

The National University of Singapore invites applications for a research position working with Assistant Professor Ou Pengfei on computational and data-driven catalyst modelling under an MOE AcRF Tier 1 project. The work aims to integrate first-principles calculations with machine-learning approaches to understand nitrogen activation on catalyst surfaces.

The successful candidate will perform DFT calculations, build and curate computational datasets, develop descriptors, and apply interpretable