About the role
AI summarisedJoin the Advanced Manufacturing & Semiconductor Division (AMS) at the Institute of High Performance Computing (IHPC), A*STAR, to support cutting-edge research and development in AI for Science. This role focuses on implementing and scaling Physics Foundation Models (PFM) to model complex physical systems within advanced manufacturing and semiconductor applications by integrating neural operators, graph-based numerical solvers, and deep learning architectures.
ResearchOnsite
Key Responsibilities
- Implementing and optimizing neural operator architectures for modeling PDE-governed physical systems.
- Developing graph-based representations of numerical solvers and integrating them into machine learning frameworks.
- Building and maintaining machine learning pipelines for scientific simulations, including data generation, training, and evaluation.
- Integrating deep learning models with physics-based simulation workflows.
- Optimizing computational performance using GPU acceleration and high-performance computing platforms.
- Supporting the development of research prototypes and experimental platforms.
- Collaborating with interdisciplinary teams working on machine learning, physics, and engineering applications.
Requirements
- Bachelor's or Master's degree in Computer Science, Electrical Engineering, Computational Physics, Applied Mathematics, or related disciplines.
- Strong programming skills in Python.
- Experience with deep learning frameworks such as PyTorch or JAX.
- Good software engineering practices, including version control and reproducible research workflows.
- Strong problem-solving skills and ability to work effectively in a collaborative research environment.