Job Description

We are seeking a highly motivated and talented Research Fellow to join our team in the development of rechargeable batteries using computational design. As part of this project, you will play a key role in designing composites materials using inorganic solid electrolytes using computational modelling and machine learning. 

Qualifications

•    Ph.D. in Materials Science, Chemistry, Physics, or a related field.
•    A deep understanding of solid-state physics/chemistry and general physical chemistry. Knowledge of rechargeable battery and electrochemistry is a plus. Experience in computational modelling of inorganic solid electrolyte or other energy materials is desired.
•    Well-equipped with different tools of materials modelling. Prior experience of computational modelling of functional materials using DFT (VASP) and molecular dynamics with machine learning force fields is desired.
•    Experience and skills in scientific programming (e.g. Python or C/C++) and data analysis, including experience with UNIX/Linux operating systems and command-line environments (e.g. Bash). Experience in machine learning & deep learning, database, and good understanding of high-performance computing hardware is a plus.
•    A track record of publishing papers in decent scientific journals and excellent writing & presentation skills.
•    Able to collaborate with experimentalist and work with other team members.

More Information

Location: Kent Ridge Campus

Organization: College of Design and Engineering

Department : Materials Science and Engineering

Employee Referral Eligible: No

Job requisition ID : 32120