The AI4X Postdoctoral Fellowship supports outstanding early-career researchers who leverage Artificial Intelligence (AI) to accelerate breakthroughs across science, technology, engineering, and mathematics, including medicine (STEM). Through the AI4X-PDF, we seek to nurture the next generation of research leaders working at the intersection of AI and STEM, driving innovation and strengthening Singapore’s AI-for-Science ecosystem.

Key Responsibilities: 

The candidate is expected to conduct the following research works

• Develop and implement the "AI+Physics" discrepancy modeling framework to predict spatiotemporal systems by combining physics-driven baselines with data-driven correctors.

• Formulate and solve inverse problems using Physics-Informed Neural Networks and relevant methodologies.

• Conduct rigorous theoretical analysis, including stability estimates and convergence proofs, to guarantee the reliability of the developed algorithms.

• Design and execute high-fidelity numerical simulations for PDE-based models and validate results against observational data.

• Draft and submit high-impact research papers to top-tier journals and present research findings at international conferences.

• Mentor junior researchers and PhD students on computational mathematics and AI methodologies.

Job Requirements:

• A PhD degree in Applied Mathematics, Computer Science, Engineering, or a related quantitative field.

• Deep expertise in numerical analysis, partial differential equations (PDEs), and scientific computing.

• Solid background in machine learning theories, with specific experience in Physics-Informed Machine Learning.

• Strong programming skills in Python, with proficiency in deep learning frameworks such as PyTorch, TensorFlow, or JAX..

We regret that only shortlisted candidates will be notified.

Hiring Institution: NTU