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Senior Researcher, Energy-Efficient AI Platform (Algorithm, Architecture and Unconventional Computing Devices)

Location

University of Toronto (St. George Campus), Toronto, Canada

Overview

We are seeking highly motivated researchers and engineers to join our Advanced Computing R&D team working on next-generation AI accelerators. As AI continues to scale, improving energy efficiency has become a critical challenge. Our goal is to increase performance per watt through co-design across algorithms, architecture, and emerging device technologies.

This position offers a unique opportunity to conduct cutting-edge research in collaboration with leading academic and industrial partners in North America, Japan, and beyond.

Key Responsibilities

• Conduct research on energy-efficient AI algorithms for next-generation workloads
• Design and evaluate AI accelerator architectures optimized for performance-per-watt
• Explore co-design methodologies across algorithms, hardware architectures, and emerging technologies
• Develop simulation, modeling, and benchmarking frameworks for accelerator evaluation
• Collaborate with researchers at the University of Toronto and partner institutions in Japan and the United States
• Contribute to and present research results at top-tier conferences (e.g., DAC, ISSCC, NeurIPS, etc.)
• Work closely with global teams, including a Japan-based research group, to drive joint research initiatives

Qualifications

• Ph.D. (or equivalent experience) in Computer Engineering, Electrical Engineering, Computer Science, or related fields
• Strong background in one or more of the following:
  
  
• AI/ML algorithms and model optimization
• Computer architecture (especially accelerators, GPUs, or domain-specific architectures)
• VLSI design or hardware-software co-design
• Emerging devices and technologies for computing
• Experience with performance, power, and efficiency optimization
• Familiarity with simulation tools, ML frameworks, or hardware design environments
• Strong publication record or demonstrated research capability

Preferred Qualifications

• Experience in cross-layer co-design (algorithm and architecture)
• Knowledge of low-power design techniques or advanced semiconductor technologies
• Experience in collaborative international research projects

Work Environment

• Located within the University of Toronto campus, enabling close collaboration with world-class faculty and researchers
• Hybrid work model: combination of on-site collaboration and remote work flexibility
• Active engagement with global research communities, especially in North America
• Opportunities to participate in leading international conferences and workshops
• Close collaboration with a Japan-based research team, enabling global-scale innovation

Why Join Us

• Tackle one of the most critical challenges in AI: energy-efficient scaling
• Work at the intersection of AI, hardware, and emerging technologies
• Collaborate with top researchers across academia and industry worldwide
• Contribute to breakthrough innovations shaping the future of computing