About the role
We are looking for motivated candidates to join the Advanced Manufacturing & Semiconductor Division (AMS) at the Institute of High Performance Computing (IHPC), A*STAR as a Research Engineer. The candidate will support research and development in AI for Science and scientific machine learning, with a focus on implementing and scaling Physics Foundation Models (PFM) for modelling complex physical systems in advanced manufacturing and semiconductor applications.
ResearchOnsite
Key Responsibilities
- Implementing and optimizing neural operator architectures for modelling 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.
Requirements
- Bachelor's or Master's degree in Computer Science, Electrical Engineering, Computational Physics, Applied Mathematics, or related disciplines.
- Strong programming skills in Python, with experience in deep learning frameworks such as PyTorch or JAX.
- Experience with scientific computing, numerical simulation, or PDE-based modelling is desirable.
- Familiarity with graph neural networks, neural operators, or physics-informed machine learning is an advantage.
- Experience with GPU computing, parallel computing, or high-performance computing environments is a plus.
- Good software engineering practices, including version control and reproducible research workflows.