Research Fellow (Department of Physics)

NATIONAL UNIVERSITY OF SINGAPORE; Singapore; On-site; SGD 20,000 - 60,000; Full time

Job summary

A leading research university in Singapore is seeking a candidate for DFT-based computational studies on epitaxial moiré superstructures. This role involves screening materials databases, conducting computations, and developing AI models, requiring a PhD in Physics or Materials Science and 4+ years of relevant experience. The ideal candidate will also assist junior students and prepare publications.

Qualifications

• PhD degree in a relevant field is required.
• Have a comprehensive understanding of novel physical properties.
• 4+ years of experience in DFT-based computational studies.

Responsibilities

• Screen databases for suitable material combinations.
• Carry out DFT-based computations of electronic structures.
• Develop AI models for large-scale screening.
• Analyze data and draft manuscripts for publication.
• Guide and assist junior students in the project.

Skills

Understanding of novel physical properties of materials

Computational software knowledge (e.g., VASP, QE)

Machine learning skills

Skills in tight-binding

Education

PhD degree in Physics or Materials Science

Job description

Interested applicants are invited to apply directly at the NUS Career Portal.

Your application will be processed only if you apply via NUS Career Portal.

We regret that only shortlisted candidates will be notified.

Job Description

The successful candidate will work with Associate Professor Wang Xuesen & Dr Shen Lei on computational studies of epitaxial moiré superstructures under a project on the Investigation of Practical Epitaxial Moiré Superstructures with Novel Electronic Properties.

The main responsibilities of the position include:

• To screen through various databases of 2D and bulk materials to identify overlayer-substrate material combinations suitable for epitaxial moiré superlattices
• To carry out DFT-based computations of the electronic structures and other properties of epitaxial moiré superlattices
• To develop AI models to extend large-scale screening and simulation
• To analyze data and draft manuscripts for publication
• To provide guidance and assistance to junior students in this project.

Qualifications

• Qualifications / Discipline: PhD degree in Physics or Materials Science or a closely related field.
• Skills: Have a comprehensive understanding of the novel physical properties of material structures based on various 2D materials. Capable of using various computational software packages, such as VASP or QE, based on density‑functional theory (DFT) for the investigation of electronic and related functional properties of 2D materials and their heterostructures. Capable of integrating other approximation frameworks in the DFT‑based computational packages to investigate complicated material systems (e.g., non‑periodic and quasi‑periodic structures). Skills in tight‑binding and/or machine learning skill are given higher priority.
• Experience: Has at least 4 years of doing DFT‑based computational studies of the electronic structures and other related properties of 2D functional materials, especially their heterostructures and other complicated systems requiring adequate approximate treatment.