Research Fellow (Computational Materials Science)
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
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