Cambridge Research Intern - MSR Intelligent Networked Systems

Research Internships at Microsoft provide a dynamic environment for research careers with a network of world-class research labs led by globally-recognized scientists and engineers, who pursue innovation in a range of scientific and technical disciplines to help solve complex challenges in diverse fields, including computing, healthcare, economics, and the environment.

We are a systems and networking research group at Microsoft Research. We do research in multiple areas of networking, security, systems, and artificial intelligence (AI). We build working systems, engage with academia, publish scientific papers, publish software for the research community and deploy cutting-edge technologies to Azure and our customers.

Our group has published in top academic conferences including ACM SIGCOMM, ACM MobiCom, ACM MobiSys, USENIX NSDI, IEEE S&P, USENIX Security, ISCA and SOSP. We have had massive impact on the Azure Network by productizing research technologies including Software Defined Networking, Hardware-accelerated Datapath, and Network Verification, and on Azure for Operators with Network Function Virtualization & Cloudification, Open radio access network (RAN), Network Programmability, and AI Operations. We have also made significant contributions to the design of Dynamic Random Access Memory (DRAM) security for datacenter hardware and the broader DRAM industry. Find out more about us here:

We strongly believe in building and fostering a diverse and inclusive work environment. We practice open communication and respectful dialogue. We support multiple social and career building opportunities in our internship program.

We seek Research & Development Interns with stellar technical skills and backgrounds in AI, wide-area networking, wireless networking, distributed systems, operating systems, mobile systems, network verification and/or security. We are looking for applicants who have experience in large-scale systems and/or networks in addition to being fluent in the relevant state-of-the-art research. Applicants should be a team player in a collaborative and supportive environment with outstanding programming skills. The work will require excelling in fast-paced execution and implementation on Azure platforms. Applicants should demonstrate depth of knowledge in systems and networking and demonstrate experience in experimentation and implementation.

Research Interns put inquiry and theory into practice. Alongside fellow doctoral candidates and some of the world’s best researchers, Research Interns learn, collaborate, and network for life. Research Interns not only advance their own careers, but they also contribute to exciting research and development strides. During the 12-week internship, Research Interns are paired with mentors and expected to collaborate with other Research Interns and researchers, present findings, and contribute to the vibrant life of the community. Research internships are available in all areas of research, and are offered year-round, though they typically begin in the summer.

Additional Responsibilities

· Develop AI, security, systems, and/or networking solutions that extend the state of the art in cloud-scale systems.

· Implement and evaluate prototypes using small-scale testbeds and large-scale production environments.

· Collaborate closely with team members on developing systems from prototyping to production level. Work closely with Azure engineering teams to drive scalable implementationsExamples of more specific responsibilities include.

· Use AI to improve network management and operation.

· Design and implement security and trust features in an OS kernel or in a hypervisor.

· Design, implement and evaluate novel solutions for improving network protocols,traffic management and/or verification on wide-area networks.

· Optimize cellular RAN behavior using AI/ML techniques.

· Implement prototypes of centralized traffic managers that can scale to large cloud networks.

· Extend a trusted execution environment (e.g., Intel SGX, AMD SEV) to a hardware accelerator, such as an FPGA or a GPU.

· Design and implement novel approaches to video-processing (e.g., ML, adaptive bitrate algorithms) for the 5G/edge.

· Extend container-orchestration systems to adaptively schedule workloads across clouds and edges and support high-performance container networking.

· Evaluate internship artifacts to support the publication of blog posts, white papers, and research papers.