Research Engineer, AI-enabled Fusion Plasma Diagnostics

A*STAR - Agency for Science, Technology and Research; Singapore; On-site; SGD 120,000 - 180,000; Full time

Job summary

FEAT Centre at A*STAR seeks a Research Engineer to advance AI-enabled fusion plasma diagnostics and data analysis, with flexibility to focus on diagnostics or AI model development or both. You will handle experimental data from microwave, imaging, and other diagnostics, and craft AI methods across heterogeneous measurements while respecting underlying physics.

The role involves collaboration with plasma physicists, diagnostic scientists, and AI researchers, and opportunities to contribute to

Qualifications

• Strong numerical and data-analysis skills and proficiency in scientific programming (Python, C/C++, Julia).
• Experience with experimental or complex scientific datasets is valued.
• Ability to work in interdisciplinary teams and communicate effectively.

Responsibilities

• Develop computational methods for analysing fusion plasma diagnostic data.
• Process and analyse datasets from multiple diagnostics and devices.
• Develop and evaluate machine-learning models for diagnostic analysis, reconstruction, forecasting.
• Apply AI approaches for learning from heterogeneous scientific data and transferring models.
• Develop scalable workflows using GPU and HPC resources.
• Collaborate with internal teams and international partners and contribute to publications.

Skills

Interdisciplinary collaboration

English communication

Education

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

Tools

Python

C/C++

Julia

PyTorch

JAX

TensorFlow

Job description

Position Summary

The FEAT Centre is seeking a Research Engineer to develop AI-enabled approaches for fusion plasma diagnostics and data analysis. The work spans two closely connected areas: fusion diagnostics and data analysis, and AI model development, with flexibility to focus on either area or work across both.

Who we are looking for

The FEAT Centre is seeking a Research Engineer to contribute to the use of experimental diagnostics and AI for fusion plasma research. You will work with diverse experimental data from fusion plasma diagnostics, including microwave, imaging, and other measurement techniques, to develop new approaches for plasma analysis and interpretation. The research presents opportunities to develop AI methods that learn across heterogeneous measurements and experimental devices while incorporating knowledge of the underlying physics.

This position is part of the Plasma Physics and Diagnostics Department (PPDD), which hosts expertise in plasma modelling and diagnostics. You will work closely with plasma physicists, diagnostic scientists, and AI researchers, and collaborate with international partners across universities and fusion research facilities.

The Research Covers Two Complementary Technical Tracks

• Fusion diagnostics and data analysis: Analyse and interpret experimental diagnostic data, including signal processing, data curation, diagnostic reconstruction, validation, and the development of robust analysis workflows.
• AI model development: Develop machine-learning methods for fusion diagnostic data, including multimodal and time-series modelling, representation learning, forecasting, transfer learning, and physics-informed approaches.

Depending on your expertise, you may contribute primarily to one track or work across both. You will contribute to publications and collaborative research projects, and help develop FEAT's capabilities in AI-enabled plasma diagnostics.

What you'll be doing

• Develop and apply computational methods for the analysis and interpretation of fusion plasma diagnostic data.
• Process, curate, and analyse experimental datasets from multiple diagnostics and fusion devices.
• Develop and evaluate machine-learning models for diagnostic analysis, reconstruction, classification, and forecasting.
• Develop and apply AI approaches for learning from heterogeneous scientific data and transferring models across fusion devices.
• Develop scalable and reproducible analysis and machine-learning workflows using GPU and high-performance computing resources.
• Collaborate with internal teams and international research partners, contribute to publications, and support collaborative projects.

What you'll bring

• Bachelor's or Master's degree in Physics, Engineering, Computer Science, Machine Learning, Applied Mathematics, Computational Science, or a closely related field.
• Strong background in at least one of the following areas: plasma or experimental physics, scientific data analysis, machine learning, or scientific computing.
• Strong numerical and data-analysis skills, with proficiency in scientific programming (e.g., Python, C/C++, Julia).
• Experience working with experimental, simulation, or other complex scientific datasets.
• Strong written and spoken English communication skills, with the ability to work effectively in interdisciplinary teams.

Good-to-Haves

• Background in plasma physics, fusion science, plasma diagnostics, or experimental physics.
• Experience with diagnostic or scientific data analysis, including signal processing, time-series analysis, imaging, or inverse problems.
• Experience developing machine-learning models using frameworks such as PyTorch, JAX, or TensorFlow.
• Experience with areas such as multimodal learning, representation learning, self-supervised learning, foundation models, forecasting, transfer learning, or uncertainty quantification.
• Experience with scientific or physics-informed machine learning.
• Experience with high-performance computing, GPU acceleration, or large-scale computational workflows.

What you will need to succeed

• Scientific problem-solving and critical thinking
• Initiative and willingness to learn
• Research communication (written and oral)
• Collaboration and teamwork in interdisciplinary environments

What we offer

• Opportunity to develop AI and diagnostic methods for challenging problems in fusion plasma research.
• Access to experimental datasets from international fusion research programmes and advanced GPU and high-performance computing resources.
• Close collaboration with plasma physicists, diagnostic scientists, AI researchers, and international fusion research partners.
• Flexibility to pursue research in fusion diagnostics and data analysis, AI model development, or across both areas.