Huawei Canada has an immediate 12-month contract opening for a Researcher.
About the team:
Established in 2014, the Distributed Scheduling and Data Engine Lab is Huawei Cloud's technical innovation center in Canada. The lab focuses on researching and developing advanced cloud technologies, supporting the productization and iterative optimization of its technical achievements. Current research areas include cloud native databases, infrastructure resource scheduling and prediction, cloud-native middleware, media engines, and user experience studies. The lab fosters a robust technical environment, allowing collaboration with industry experts to create a highly competitive cloud platform.
About the job:
Lead research into state-of-the-art cloud rendering techniques particularly multiscale simulated physically-based material dataset rendering.
Develop and implement novel multiscale material modeling and simulation algorithms to enhance our simulated material database
Execute research projects efficiently, adhering to defined tasks, timelines, and milestones.
Requirements
About the ideal candidate:
3+ years of research experience in physically-based rendering and multiscale computational simulation of advanced materials. This includes, but is not limited to, expertise in machine learning for real-time rendering for material, AI-accelerated rendering algorithms(materials), and computational electromagnetic modeling and simulations for the material database.
A strong publication record with at least three research papers, preferably including one in a top-tier journal or conference (e.g., SIGGRAPH, SIGGRAPH Asia, Eurographics, HPG).
At least 1 year of experience implementing AI/machine learning techniques within physically-based rendering pipelines.
Demonstrated innovation, focus, and results-orientation, coupled with strong self-motivation and resourceful problem-solving abilities.
Excellent interpersonal, networking, and communication skills.
Research background in neural material and cloth rendering, or experience with simulated material studies is an asset.
