Research Intern - Networking Research Group

Microsoft Microsoft · Big Tech · Redmond, WA +1 · Applied Sciences

Research Intern position in Microsoft's Networking Research Group, focusing on networked systems including AI's role in networking challenges. The internship involves contributing to research agendas, collaborating with researchers, and potentially working on systems, sensing, security, AI, edge computing, optimization, and probability theory.

What you'd actually do

  1. Research Interns put inquiry and theory into practice.
  2. Alongside fellow doctoral candidates and some of the world’s best researchers, Research Interns learn, collaborate, and network for life.
  3. Research Interns not only advance their own careers, but they also contribute to exciting research and development strides.
  4. 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.

Skills

Required

  • Currently enrolled in a Ph.D. program in Computer Science, Electrical Engineering or a related STEM field.
  • Ability to work with researchers at Microsoft to push forward research agendas
  • work in teams in a collaborative and supportive environment
  • programming skills
  • familiarity with the latest tools & frameworks
  • depth of knowledge in distributed systems and operating systems
  • experience in low-level programming, experimentation, and modeling

Nice to have

  • Ability to think unconventionally to derive creative and innovative solutions.
  • Experience in one of the following: network hardware, physical layer technologies, mobile systems and devices, network architecture, operations, and design, network security and privacy, AI/machine learning, analysis and optimization
  • Knowledge of large models, and experience training them at scale, or running inference is a plus.

What the JD emphasized

  • Ph.D. program in Computer Science, Electrical Engineering or a related STEM field
  • systems building
  • network hardware, physical layer technologies, mobile systems and devices, network architecture, operations, and design, network security and privacy, AI/machine learning, analysis and optimization
  • Knowledge of large models, and experience training them at scale, or running inference is a plus.