The Human-Machine Interaction Lab unites global talents to redefine the relationship between humans and technology. Focused on innovation and user-centered design, the lab strives to advance human-computer interaction research. Our team includes researchers, engineers, and designers collaborating across disciplines to develop novel interactive systems, sensing technologies, wearable and IoT systems, human factors, computer vision, and multimodal interfaces. Through high-impact products and cutting-edge research, we aim to enhance user experiences and interactions with technology.
About the JobDevelop and deploy machine learning models for: Solar and wind power forecasting, supporting both real-time operations and longer-term energy planning
Build data-driven components for renewable plant digital twin platforms, including: Real-time generation simulation and monitoring; Weather-driven scenario analysis; Performance diagnostics and anomaly detection
Work with diverse data sources, such as: SCADA and historical generation signals; Meteorological measurements and NWP forecasts; Satellite imagery and sky-imager video streams; Plant layout, spatial topology, and turbine/panel metadata
Collaborate with cross-functional engineering and research teams to deliver practical, production-ready solutions.
The total target annual compensation for this position ranges from $106,000 to $156,000 depending on education, experience, and demonstrated expertise.
About the Ideal CandidateMaster’s or PhD degree in: Machine Learning / Computer Science; Applied Mathematics / Statistics; Meteorology / Atmospheric Science; Energy Systems / Electrical Engineering
Strong foundation in machine learning, deep learning, and statistical modeling
Proficiency in Python and modern deep learning frameworks (PyTorch is an asset)
Experience with computer vision and image/video processing, such as: Remote sensing imagery understanding; Spatio-temporal video modeling; Vision Transformers or related architectures
Familiarity with physics-informed learning, including: Incorporating physical constraints into neural models; Hybrid modeling combining data-driven and domain knowledge
Ability to work with real-world industrial sensor data and build robust forecasting pipelines.
Huawei Canada is committed to a fair, inclusive, and accessible recruitment process. If you require accommodation during any stage of the hiring process, please let us know and we will work with you to meet your needs.
All applications for this position are reviewed directly by our hiring team, we do not use artificial intelligence tools to screen or select candidates.
Skills Required
- Master's or PhD in Machine Learning, Computer Science, Applied Mathematics, Meteorology, or related fields
- Strong foundation in machine learning, deep learning, and statistical modeling
- Proficiency in Python and deep learning frameworks, especially PyTorch
- Experience with computer vision and image/video processing
- Familiarity with physics-informed learning
What We Do
Founded in 1987, Huawei is a leading global provider of information and communications technology (ICT) infrastructure and smart devices. We are committed to bringing digital to every person, home and organization for a fully connected, intelligent world. We have approximately 197,000 employees and we operate in over 170 countries and regions, serving more than three billion people around the world. In Canada, Huawei conducts innovative and leading edge research in 5G technologies, along with advanced development of emerging cloud, device and network technologies & services. While our renowned Canada Research Centre in the thriving technology landscape of Ottawa, Ontario continues to grow rapidly in size and strategic product initiatives, additional presence has also been established across Canada with R&D facilities in Vancouver, Edmonton, Waterloo, Markham, Montreal, and a R&D office in Quebec City.
