Research Fellow (Computational Materials Simulation for Disordered Crystals) Full-time

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 Research 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.

Hiring Institution: NTU