Due to limited vacancies, our PhD and MPhil positions are currently full, and we are not recruiting PhD or MPhil students for the upcoming admission cycles. Our group is affiliated only with the Department of Chemistry and the Department of Chemical and Biological Engineering (CBE) at HKUST—we are not affiliated with CSE, ECE, or Physics, so when vacancies open up, PhD/MPhil admissions can only be made through Chemistry or CBE.

However, we welcome HKUST undergraduate and master's students who would like to take research credits (e.g., UROP, FYP, or Master's research projects) with our lab. For our current active projects, please see the HKUST UROP, FYP, & Master Research page. When reaching out, applicants are welcome to include any of the following materials that you have:

• Curriculum Vitae (CV)
• Academic transcript
• Research proposal
• Representative publications or other research outputs
• Expected starting date (enrollment or onboarding)
• For postdoctoral applicants: contact information for at least two reference letter writers

The following courses and topics are helpful for understanding the core research of the AI for Physical Sciences Lab. You may also check the Mini Tests to explore your interests.

1. CS/Math: Linear Algebra, Probability and Statistics, Data Structures, Introduction to Machine Learning/AI, Mathematical Modeling, Stochastic Processes and Markov Chains, Linear Programming, Convex Optimization, Statistical Learning Theory, Information Theory, Functional Analysis, Numerical Analysis/Linear Algebra/PDE, Stochastic DE, Differentiable Manifolds, Lie Algebra, Computational Complexity, Topics in ML (Gaussian Processes, Graph Neural Networks, Reinforcement Learning, Generative Models, Language Models). Abstract Algebra, Topology, and Computational Graphics are not required but are a plus.
2. Physics/Chemistry/Materials: Quantum Mechanics, Statistical Mechanics, Atomic Physics, Electronic Structure Theory, Computational Physics, Group Representation Theory (note: not just group theory; chemistry students may encounter this in inorganic or structural chemistry courses), Solid-State Physics, Quantum Field Theory, Polymer Chemistry/Physics, Introduction to Quantum Computing.
3. Other foundational skills: GitHub (open-sourcing spirit), Python (NumPy, SciPy, Scikit-learn, Pandas, etc.), PyTorch, JAX. Proficiency in using the Linux operating system, command line, Slurm, Docker/Conda for environment setup, and the ability to collaborate effectively with AI agents (e.g., vibe coding, automation pipeline for your Gaussian calculations, auto-matching paper formulas with code, etc.). C++ and Julia are not required but a plus. Java is not required and not a plus.