Senior Principal Researcher - AI for Science

Huawei Technologies Co.; Markham; Hybrid; CAD 150,000 - 210,000; Full time

Job summary

Huawei Canada is seeking a Senior Principal Researcher - AI4Science to advance research at the intersection of scientific computation and AI infrastructure. This role blends physics-informed learning, distributed training, and large-scale simulation to push the frontier of AI for science.

The ideal candidate will lead impactful research, mentor junior researchers, publish in top venues, and collaborate across Huawei's Computation + Networking divisions to co-design models and systems that scale.

Qualifications

• PhD in Physics, Computer Science, Computational Science or related field.
• Proven AI for Science research experience in scientific simulation or physics-informed learning.
• Strong programming and distributed systems experience (Python, CUDA, PyTorch, TensorFlow).
• Familiarity with HPC, parallel computing, or large-scale AI infrastructure.
• Strong research record demonstrated through publications or impactful project experience.

Responsibilities

• Conduct cutting-edge research at the intersection of Scientific computation and AI infrastructure, including physics-informed AI, distributed training, and hybrid simulation–ML workflows.
• Collaborate across Huawei’s Computation + Networking R&D divisions to design infrastructure-aware AI models and co-optimize algorithms and hardware.
• Lead or contribute to AI4Science foundation models in areas such as materials, physics, molecular, or multi-scale simulation.
• Prototype distributed training solutions and integrated AI pipelines using Huawei’s MindSpore and Ascend AI ecosystems.
• Publish research in top-tier ML and science venues and contribute to Huawei’s internal IP and R&D assets.
• Mentor junior researchers and contribute to long-term strategic planning of Huawei’s AI4Sci + Compute Infrastructure initiatives.

Skills

Python

CUDA

PyTorch

TensorFlow

Distributed systems

HPC

Education

PhD in Physics/CS/Computational Science

Tools

MindSpore

Ascend AI

Job description

Huawei Canada has an immediate permanent opening for a Senior Principal Researcher - AI4Science

About the team:

The Technology Planning and Cooperation Department promotes strategic innovation across all of Huawei Canada. Working with fellow experts, the focus is researching new and upcoming areas of technology as well as strategic planning to help achieve long term vision of Huawei. This department offers a unique opportunity to leverage both technical and business skills.

While we are developing next-generation computing infrastructure and AI foundation models that integrate physics, simulation, and learning at unprecedented scale, this is the position we are targeting to bring in a bright individual who bridges scientific AI research and system-level innovation—advancing our mission of combining computing and connectivity to enable large-scale AI for Science and simulation intelligence.

About the job:

• Conduct cutting-edge research at the intersection of Scientific computation and AI infrastructure, including physics-informed AI, distributed training, and hybrid simulation–ML workflows.
• Collaborate across Huawei’s Computation + networking R&D divisions to design infrastructure-aware AI models and co-optimize algorithms and hardware.
• Lead or contribute to AI4Science foundation models in areas such as materials, physics, molecular, or multi-scale simulation.
• Prototype distributed training solutions and integrated AI pipelines using Huawei’s MindSpore and Ascend AI ecosystems.
• Publish research in top-tier ML and science venues (e.g., NeurIPS, ICML, JHEP, PRD) and contribute to Huawei’s internal IP and R&D assets.
• Mentor junior researchers and contribute to long-term strategic planning of Huawei’s AI4Sci + Compute Infrastructure initiatives.

About the ideal candidate:

• Ph.D. in Physics, Computer Science, Computational Science, or a related field.
• Proven research experience in AI for Science, scientific simulation, or physics-informed learning.
• Strong programming and distributed system experience (Python, CUDA, PyTorch, TensorFlow).
• Familiarity with HPC, parallel computing, or large-scale AI infrastructure.
• Strong research record demonstrated through publications or impactful project experience.