M.Sc. / Ph.D. Student – Systems Research

Our team at the Huawei Smart Platforms Innovation Lab is chartered to research and incubate new technologies that will redefine the performance and functionality of future data centers, cloud platforms, and supercomputing systems.
We work on cutting-edge challenges across computer systems, AI infrastructure, cloud computing, storage, networking, and distributed systems, combining academic research with hands-on development and experimentation.

What will you be doing?

We are looking for a talented and motivated M.Sc. or Ph.D. student to join our Systems Research team and contribute to advanced research in next-generation computing systems.

In this role, you will:

• Participate in research and analysis of state-of-the-art computer systems and emerging technologies.

• Investigate system performance, identify bottlenecks, and explore innovative approaches for improving system efficiency, scalability, and performance.

• Develop and evaluate Proof-of-Concepts (PoCs) for end-to-end systems and novel architectures for data centers, including AI, Cloud, Storage, Big Data, and distributed computing.

• Gain hands-on experience in implementing, testing, benchmarking, and validating new system concepts and architectures.

• Work closely with experienced researchers, architects, and engineers on advanced research and development projects.

• Explore recent academic research and emerging technologies, identify new research opportunities, and contribute ideas and insights to ongoing research activities.

• Currently pursuing an M.Sc. or Ph.D. degree in Computer Engineering, Computer Science, Electrical Engineering, or a related field.
• Strong academic background and interest in computer systems, distributed computing, AI infrastructure, cloud computing, or related areas.

• Good programming skills, preferably in C/C++.

• Strong analytical, research, and problem-solving abilities.

• Ability to understand, critically analyze, and apply insights from technical and academic literature.

• Motivation to explore new technologies and conduct hands-on research and experimentation.

• Ability to work independently while collaborating effectively within a research and development team.

Ways to stand out from the crowd

• Knowledge or academic experience in one or more of the following areas: Virtualization, Storage, Hardware Offloads, Network Acceleration, RDMA (iWARP, RoCE, InfiniBand), or distributed systems.

• Previous research experience, academic projects, or publications in computer systems or related fields.

• Familiarity with AI/ML systems, AI inference, LLM serving, or AI computation pipelines.

• Understanding of performance analysis, profiling, benchmarking, and system bottleneck identification.

• Experience with Linux systems and low-level or systems programming.

• Publications or research contributions in relevant academic venues are considered an advantage