Job Title: Principal Researcher - Data Centre Networks

Candidates must be based in Europe alreadyIn this role, you will be responsible for the research and set up the direction of DCN services and architecture, key DCN algorithms and protocols. You will also help the team to complete key technological innovations, and build key technical breakpoints.

Responsibilities:

• Conduct cutting-edge research on the next-generation Data Center Network architecture and new technologies
• Develop and prototype novel Data Center Networking methods
• Optimize the performance and efficiency of parallel computing systems, especially the large-scale AI clusters mainly from the perspective of the integration of network, computing, and storage systems
• Identify technology trends in the field of Data Centre Networking
• The scope includes but is not limited to network topology, traffic control technology, software-defined networks, optical and electrical hybrid networks, in-network computing, etc.

Requirements

• PhD in Computer Science, Electronic Engineering, Artificial Intelligence, Automation, Mathematics, Physics and other relevant discipline.
• At least 5 years of work experience in Data Center Network Research either in industry or academia.
• Proficiency in data center networks and high-performance interconnection technology systems.
• Sound experience in performance or efficiency optimization of parallel computing systems.
• Strong knowledge in large-scale distributed deep learning and be familiar with corresponding infrastructure and key technologies.
• Excellent communication skills in English, both written and verbalAbility to engage with a multicultural team both locally and across multiple global sitesInteresting

Research Topics:

• Modern network technology or high-performance interconnection, cloud DCN technologies, including network architecture, resource pooling techniques, optical network techniques, etc.
• Performance or efficiency optimization of parallel computing systems.
• Research on distributed machine/deep learning, distributed storage, high-performance computing systems, including network architecture, networking solutions, and the design of new device forms.
• Infrastructure and key technologies of large-scale training/inference combined with systematic thinking on how to improve the system scale and efficiency (Optional).
• Network theory and optimization algorithms, focusing on DCN business service assurance technology, network congestion control, traffic scheduling/forecasting, TCP/RDMA acceleration, and low-latency assurance for DCN, etc.
• New data center architectures, new topologies, new protocols, new hardware, and algorithms, such as CXL bus protocol extensions, non-CLOS topologies, GPU cluster interconnections, and DPU offloading, among other new technological directions