Research Fellow (Atomic catalysts and Machine Learning)
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What you'll do
- Theoretical predictions using DFT and machine learning, and mechanistic understanding of atomic catalysts
- Investigation of mechanism by in-situ and/or operando techniques and theoretical calculations
- Coordinate the collaboration with other researchers in this project to maintain steady progress, and provide support to the research group on related experiments
- Provide support to the project management and lab infrastructure, including procurement, setting up battery fabrication line, set up equipment for in-situ and/or operando characterizations, annual and final project reports
- Make regular progress reports to PI
- Write one proposal based on results obtained from this project for external grant
What they're looking for
- A PhD degree in material sciences or applied physics, with focus on renewable energy
- Evidenced experience in DFT and machine learning especially its application in atomic catalysts
- Strong publication record on the topic of renewable energy materials especially electrocatalysis
- Entry level candidates are welcome to apply
- Strong motivation to undertake grand challenges in multidisciplinary subjects
- Excellent team player who is capable and willing to provide supports in a dynamic and interdisciplinary environment
Summarised by NextRaise from the employer’s description, which follows in full below.
Full description from employer
Join Our Team at the School of Physical and Mathematical Sciences, Nanyang Technological University, Singapore
The School of Physical and Mathematical Sciences (SPMS) at NTU Singapore hosts research and education activities in two divisions: Division of Mathematical Sciences (MAS) and Division of Physics and Applied Physics (PAP). MAS covers diverse topics ranging from pure mathematics to the applications of mathematics in cryptography, computing, business, and finance. PAP covers many areas of fundamental and applied physics, including quantum information, condensed matter physics, biophysics, and photonics. Over the years, SPMS has attracted talented individuals from around the world and Singapore to join as scientific leaders and researchers.
Join the laboratory of Fan Hongjin at SPMS. We are seeking a Research Fellow to contribute to a project focused on focused on data-driven discovery of atomic catalysts.
Key Responsibilities:
Theoretical predictions using DFT and machine learning, and mechanistic understanding of atomic catalysts
Investigation of mechanism by in-situ and/or operando techniques and theoretical calculations
Coordinate the collaboration with other researchers in this project to maintain steady progress, and provide support to the research group on related experiments
Provide support to the project management and lab infrastructure, including procurement, setting up battery fabrication line, set up equipment for in-situ and/or operando characterizations, annual and final project reports
Make regular progress reports to PI
Write one proposal based on results obtained from this project for external grant
Job Requirements:
A PhD degree in material sciences or applied physics, with focus on renewable energy
Evidenced experience in DFT and machine learning especially its application in atomic catalysts
Strong publication record on the topic of renewable energy materials especially electrocatalysis
Entry level candidates are welcome to apply
Strong motivation to undertake grand challenges in multidisciplinary subjects
Excellent team player who is capable and willing to provide supports in a dynamic and interdisciplinary environment
The College of Science seeks a diverse and inclusive workforce and is committed to equality of opportunity. We welcome applications from all and recruit on the basis of merit, regardless of age, race, gender, religion, marital status and family responsibilities, or disability.
We regret to inform that only shortlisted candidates will be notified.
Hiring Institution: NTUCompany
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