Postdoctoral Fellow (Computational Materials Simulation for Disordered Crystals)

NANYANG TECHNOLOGICAL UNIVERSITY; Singapore; On-site; SGD 55,000 - 75,000; Full time

Job summary

A leading research university in Singapore is seeking a Postdoctoral Fellow to advance computational infrastructures for materials design. The successful candidate will focus on developing methodologies for disordered crystal materials using DFT codes. Responsibilities include creating workflows for high-throughput computations and collaborating on method development. The ideal candidate holds a PhD in a relevant field and possesses strong programming skills in languages such as Python or Julia.

Qualifications

• PhD required in a relevant field.
• Strong experience with DFT codes essential.
• Hands-on materials simulation experience important.

Responsibilities

• Develop approximation methods for materials properties.
• Design DFT workflows for materials discovery.
• Accelerate materials discovery using high-throughput computation.
• Collaborate with teams on method refinement.

Skills

Experience with computational materials science

Proficiency in DFT codes

Programming for data science

Education

PhD in Materials Science, Chemistry, Physics, Computer Science, or a related field

Tools

VASP

Quantum ESPRESSO

Python

Julia

Fortran

ase

pymatgen

atomate2

fireworks

aflow

Job description

The School of Materials Science and Engineering (MSE) provides a vibrant and nurturing environment for staff and students to carry out inter-disciplinary research in key areas such as Computational Materials Science, Characterisation Materials Science, Defence Composite Materials, Functional Composite Materials, Energy, Nanomaterials, Low Dimensional Materials, Biomaterials Materials, Biological Materials, Bioinspired Materials and Sustainable Materials.

For more details, please view https://www.ntu.edu.sg/mse/research.

We are looking for a Postdoctoral Fellow to contribute to building computational infrastructures for Materials Generative Design and Testing Framework. The role will focus on the development of first-principles methodologies and implementations of structures modelling and properties interpolating for composition-disordered crystal materials, which render feasible the pipelines for property interpolation for disordered crystals and the associated databases.

Key Responsibilities:

• Develop and apply approximation methods for interpolating electronic/phononic/thermodynamic properties of disordered crystal materials.
• Design and implement high-throughput density functional theory (DFT) workflows.
• Perform high-throughput computation for accelerating materials discovery and generate datasets for materials informatics.
• Work with teams to refine the developed methods and workflows.

Job Requirements:

• PhD in Materials Science, Chemistry, Physics, Computer Science, or a related field.
• Strong experience with DFT codes (e.g., VASP/Quantum ESPRESSO).
• Hands-on experience with mainstream implementations for disorder approximation (e.g., special quasi-random structure/partial occupation/cluster expansion), and accessories for materials simulation (e.g., ase/pymatgen) and high throughput framework (e.g., atomate2/fireworks/aflow).
• Proficiency in at least one programming language for data science and for numerical computing (e.g., Python/Julia/Fortran).

We regret to inform that only shortlisted candidates will be notified.