Contact Us
We are always looking for curious and motivated students to join us in pushing the frontiers of computational interfacial chemistry!
Graduate Students (PhD & Masters)
We are actively recruiting PhD students interested in developing AI-enhanced simulation frameworks, understanding interfacial phenomena, and designing materials for sustainable energy conversion and storage.
We encourage prospective students to reach out to Dr. LI to discuss future research directions and available funding opportunities (eg., President’s Graduate Fellowship (PGF), NUS Research Scholarship (RS), NUS ASEAN Research Scholarship, NUS Industry-Relevant PhD Scholarship (IRP) Singapore International Graduate Award (SINGA), and others).
To express interest, please send your CV to xiaoyanli@nus.edu.sg
Undergraduate Students
We welcome undergraduate students from renowned universities around the world with a strong interest in computational materials science, clean energy technologies, or AI applications in chemistry and engineering. Students who are eager to learn and contribute to ongoing research projects are encouraged to contact Dr. Xiaoyan Li
Visiting Scholars
We warmly welcome visiting scholars, including professor, postdocs, graduates, and undergraduate students, who are interested in collaborative research in AI-accelerated modeling, interface science, or clean energy materials. For example:
CSC-funded research program for PhD students, professors, and even postdocs;
IRIS@NUS funed by NUS for undergraduate students;
UROPS Special Term funed by NUS for undergraduate students;
...
Please send your CV and a brief statement of research interests to: xiaoyanli@nus.edu.sg
Postdoctoral Fellows (Opening)
We are seeking talented and driven postdoctoral researchers to contribute to cutting-edge research in AI-accelerated simulation and materials design for next-generation clean energy technologies.
Postdocs will have the opportunity to lead independent projects, mentor junior members, and collaborate with global interdisciplinary teams.
Requirements:
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Strong motivation for research, excellent communication skills, and a collaborative mindset
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PhD in AI for Science, Chemistry, Materials Science & Engineering, Computer Science, or related disciplines
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Excellent written and oral communication skills in English
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Candidates must have experience in at least ONE of the following categories in specific skills and experience requirements.:
Specific Skills and Experience Requirments:
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AI/ML methods and algorithms
Experience with one or more of: MLP/deep learning, generative AI, large language models (LLMs), Gaussian processes / Bayesian optimization, graph theory / graph learning (e.g., GNNs); -
High-throughput structure generation and global optimization
Experience with high-throughput candidate generation and optimization, such as genetic algorithms, global optimization, and structure-search/screening pipelines (e.g., ASE or in-house frameworks); -
Multiscale simulation methods (use and/or development)
Experience with Monte Carlo methods (including KMC/GCMC/MMC), microkinetic modeling, constrained AIMD (e.g., slow-growth AIMD), and/or molecular dynamics (MD).
Please email the following materials files to xiaoyanli@nus.edu.sg
Recommedded subject line： Postodc Application + Name + Research Area
Application package:
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Curriculum Vitae (CV): including research experience, publications, and selected representative papers)
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Research statement (1–2 pages): your research interests, relevant expertise, and proposed directions)
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Contact information for at least three referees (name, affiliation, email)