Postdoc: Computational Physics & ML for Materials

National University of Singapore; Singapore; On-site; SGD 60,000 - 90,000; Full time

Job summary

The National University of Singapore invites applications for a full-time Postdoctoral Research Fellow position in the Institute for Functional Intelligent Materials (I-FIM). The appointment is a fixed-term contract for two years with potential renewal subject to funding and performance.

Ideal candidates have a PhD in a computational field and proven expertise spanning DFT, transport theory, and machine learning, with hands-on experience in VASP/Quantum ESPRESSO and ML frameworks on GPU

Qualifications

• PhD in Physics, Materials Science, Chemistry, or related field.

Responsibilities

• This role requires hands-on expert command of the full computational toolchain, end to end, the entire pipeline from first-principles defect physics through transport theory to machine-learning-based diagnostics
• Demonstrated ability to personally execute and lead technical work across multiple domains (DFT, transport theory, and machine learning)
• Strong record of peer-reviewed publications spanning computational condensed-matter physics and, ideally, machine-learning applications, commensurate with career stage

Skills

DFT methods

First-principles

Quant. transport

Machine learning

Deep learning

Python

MATLAB

PyTorch

TensorFlow

2D materials

HPC

Publications

Cross-domain leadership

Education

PhD in Physics, Materials Science, Chemistry

Tools

VASP

Quantum ESPRESSO

Job description

The National University of Singapore invites applications for a full-time Postdoctoral Research Fellow position in the Institute for Functional Intelligent Materials (I-FIM). The appointment is a fixed-term contract for two years with potential renewal subject to funding and performance.

Ideal candidates have a PhD in a computational field and proven expertise spanning DFT, transport theory, and machine learning, with hands-on experience in VASP/Quantum ESPRESSO and ML frameworks on GPU