Best Paper Candidates

The Computing System Lab at the Zurich Research Center is a leading hub for research and development in advanced computing systems, with a strong focus on chip architecture, computing cluster, system & interconnect, memory subsystem, artificial intelligence, and framework & software technologies. With a team of over 70 researchers, including 50+ PhD holders, the lab operates at the cutting edge of computational innovation and plays a key role in shaping the future of technology.

Under experienced leadership guidance, the lab has significantly expanded its research scope and impact, earning a reputation for excellence and fostering a collaborative, dynamic environment that nurtures both innovation and talent.

In addition to its impressive research output, the Computing System Lab fosters collaboration with leading industry partners and academic institutions around the world. The lab has received over CHF 150 million in funding in the past five years, supporting its groundbreaking work and enabling large-scale projects. Through its interdisciplinary approach, the lab blends expertise from software and hardware codesign, and AI technologies to develop real-world, impactful solutions that continues to drive the technology leadership for various Huawei products.

The lab’s commitment to innovation is also reflected in its high publication rate, with over 100 peer-reviewed papers published annually in top-tier conferences and journals. The Computing System Lab continues to push the boundaries of what is possible in computing, contributing to the advancement of next-generation AI system, software, and high-performance memory architectures.

We are currently looking for Researchers with a strong publication record and best papers at top-tier conferences (e.g., ISCA, MICRO, ASPLOS, HPCA, DAC, NeurIPS, ICML, OSDI).

Our fields of research are:
v CPU, GPU and AI Accelerator Architectures
v Heterogeneous Systems and Integrated CPU+GPU+AI Devices
v New Interconnects and Routing Methods
v Supernode, Cluster and Datacenter Architectures for Computing and AI
v AI and Agents for Automated Chip Design
v Hardware-Software Interfaces and Co-Design
v Parallel Programming Models and Platforms for AI
v New Compiler Technologies
v Large Language Model (LLM) Training and Inference
v Multi-Modal AI, Agents, Artificial General Intelligence (AGI)
Security of AI Systems

Please feel free to contact me if you have questions.