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3.5-year D.Phil. studentship Supervisors: Prof Noa Zilberman The training of new AI models, as well as their deployment for inference, is transforming the design of computer networks. In this project, you will investigate innovative networking solutions for frontier AI systems, with a particular focus on the architecture of network switches. You will explore the role of the network switch in AI systems with sub-1 ns latency between accelerators, including how operations are partitioned between switches and edge devices. Building on this analysis, you will develop novel networking solutions that accelerate frontier AI systems. Eligibility This studentship is funded through the VMware University Research Fund and is open to Home and Overseas students (full award – fees plus stipend). Award Value Course fees are covered at the level set for Home or Overseas students. The stipend (tax-free maintenance grant) is the UKRI minimum stipend, and at least this amount for a further two and a...

This job is with Dataiku, an inclusive employer and a member of myGwork – the largest global platform for the LGBTQ+ business community. Please do not contact the recruiter directly. Dataiku is The Universal AI Platform™, giving organizations control over their AI talent, processes, and technologies to unleash the creation of analytics, models, and agents. Providing no-, low-, and full-code capabilities, Dataiku meets teams where they are today, allowing them to begin building with AI using their existing skills and knowledge. Why Engineering at Dataiku? Dataiku’s on-premise, cloud, or SaaS-deployed platform connects many data science technologies, and our technology stack reflects our commitment to quality and innovation. We integrate the best of data and AI tech, selecting tools that truly enhance our product. From the latest LLMs to our dedication to open source communities, you'll work with a dynamic range of technologies and contribute to the collective knowledge of...