Huawei Canada has an immediate permanent opening for a Researcher.
About the team:
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 job:
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Working closely with a team of experienced human-machine interaction
researchers to solve real world challenges in the application of Embodied AI.
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Developing state-of-the-art approaches for Embodied AI applications.
Directions include, but not limited to, generative AI, multimodal embodied
agent, reasoning, planning, data generation and augmentation, reinforcement
learning, and low-level control.
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Translating mathematical problem definitions and model/solution
specifications into efficient executable code.
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Conducting evaluation and empirical studies using robotic platforms in both
simulation and real-world.
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Proposing high-impact intellectual properties (e.g., patents), and publishing
or contributing to research papers in top-tier AI venues.
About the ideal candidate:
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PhD degree in Computer Science/Computer Engineering or related fields or
master's degree with equivalent professional experience.
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Prior experience in robotics, generative AI, and/or vision and language
processing.
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Proven research record in AI by having at least one paper as the first author
in top tier venues (e.g., NeurIPS, ICML, ICLR, IROS, ACL, EMNLP, CVPR, ICCV,
ECCV, ICRA, HRI).
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Proficiency in Python and C++ programming language, with experience in
mainstream deep learning frameworks (e.g., PyTorch, TensorFlow).
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Experience in robotics applications, in particular decision-making, planning
and control, or experience with real robot and ROS is an asset.
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Experience with using large-scale datasets and sensor data, or with use of
various transformer architectures and diffusion models is an asset.
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Experience with imitation and reinforcement learning algorithms is an asset.
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Working knowledge of the general terminal devices landscape, architectures,
trends, and emerging technologies, with relevant experience and strong
interest in Human-computer Interaction, especially (multimodel) voice
interaction.
