Research Fellow – Computational Physics

About the role

The Institute for Functional Intelligent Materials (I‑FIM) at NUS seeks a full‑time Research Fellow to advance computational studies of functional intelligent materials. The two‑year fixed‑term position focuses on integrating first‑principles defect physics, quantum transport theory, and machine‑learning diagnostics.

Key responsibilities

• Develop and execute end‑to‑end computational workflows from DFT calculations to transport simulations.
• Design and implement machine‑learning models for material property prediction using GPU clusters.
• Collaborate with experimental teams to validate computational predictions.
• Publish peer‑reviewed articles and present findings at international conferences.

Required profile

• PhD in Physics, Materials Science, Chemistry or a closely related computational field.
• Proven track record in first‑principles methods, quantum transport, and machine‑learning applications.
• Strong record of peer‑reviewed publications in computational condensed‑matter physics.

Required skills

• Expert use of DFT codes (VASP, Quantum ESPRESSO).
• Proficiency in Python and/or MATLAB for scripting and data analysis.
• Knowledge of T‑matrix scattering theory and quantum transport.
• Experience with effective‑medium theory (EMT) and random‑resistor‑network (RRN) simulations.
• Hands‑on experience training deep‑learning models with PyTorch or TensorFlow on GPU clusters.
• Familiarity with 2D transition‑metal dichalcogenides and point‑defect physics.

What we offer

• Competitive monthly salary (SGD 5,750‑8,000).
• Access to state‑of‑the‑art high‑performance computing facilities.
• Collaborative research environment within a world‑leading institute.