Research Fellow (Mathematical AI)

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.

We are looking for three highly motivated Research Fellow to join Associate Professor Xia Kelin's team at the School of Physical and Mathematical Sciences. The project focuses on developing Mathematical AI techniques, such as, geometric/topological/algebraic data analysis, geometric/topological deep learning, Math for AI, categorical deep learning, sheaf neural networks, PINN/KAN models, neural operators, etc, and applying these methods to molecular sciences, including biology, chemistry, materials, etc.

• →

  Contribute to the development and implementation of Mathematical AI techniques, such as, geometric/topological/algebraic data analysis, geometric/topological deep learning, Math for AI, categorical deep learning, sheaf neural networks,

• →

  Perform data preprocessing, algorithm/method/model design, scientific computing, experimental validation.

• →

  Preparation of research papers, reports, and presentations to disseminate findings.

• →

  Participate in regular team meetings and contribute to the overall progress of the project.

• A PhD degree in mathematics, AI or related areas, with a strong background geometric/topological/algebraic data analysis, geometric/topological deep learning, molecular sciences.

• Proficiency in programming languages such as Python, R, or similar.

• Excellent analytical and problem-solving skills.

• Ability to work both independently and collaboratively in a team.

• Previous research experience and publication record in a related field preferred.

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 that only shortlisted candidates will be notified.