Research Engineer , Advanced Manufacturing & Semiconductor, IHPC

A*STAR - Agency for Science, Technology and Research; Singapore; On-site; SGD 60,000 - 80,000; Full time

Job summary

A leading research agency in Singapore is seeking a Research Engineer to join its Advanced Manufacturing & Semiconductor Division. The role focuses on implementing AI for scientific machine learning, specifically in modeling complex physical systems. Candidates should have a relevant degree and strong programming skills in Python, with prior experience in deep learning frameworks like PyTorch. Collaboration with interdisciplinary teams is essential. This position offers opportunities to develop innovative computational modeling tools.

Qualifications

• Bachelor's or Master's degree in relevant fields.
• Strong Python programming skills.
• Experience in deep learning frameworks like PyTorch or JAX.
• Familiarity with graph neural networks or physics-informed machine learning.
• Good software engineering practices.

Responsibilities

• Implement neural operator architectures for PDE-governed physical systems.
• Develop and integrate graph-based numerical solvers.
• Build machine learning pipelines for scientific simulations.
• Optimize computational performance using GPU acceleration.
• Collaborate with interdisciplinary teams.

Skills

Python programming

Deep learning frameworks (e.g., PyTorch, JAX)

Scientific computing

Numerical simulation

Problem-solving

Education

Bachelor's or Master's in Computer Science, Electrical Engineering, Computational Physics, Applied Mathematics

Tools

GPU computing

High-performance computing environments

Job description

Job Summary

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, focusing on implementing and scaling Physics Foundation Models (PFM) for modelling complex physical systems in advanced manufacturing and semiconductor applications. This work involves integrating neural operators, graph-based numerical solvers, and deep learning architectures to develop next-generation computational modelling tools. You will work closely with researchers and engineers to build robust computational frameworks and accelerate physics-based simulations using machine learning.

The Key Scope Of Work Includes

• 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.
• Collaborating with interdisciplinary teams working on machine learning, physics, and engineering applications.

Job 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.
• Strong problem-solving skills and ability to work effectively in a collaborative research environment.