Research Intern - Deep Learning Group

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

Research Intern position in Microsoft's Deep Learning group focusing on cutting-edge research in deep learning, AI, and related fields. The intern will collaborate with researchers, work on challenging problems, and potentially publish their findings. The role requires a PhD student with experience in Machine Learning, Deep Learning, and mathematical modeling.

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.
  5. Research internships are available in all areas of research, and are offered year-round, though they typically begin in the summer.

Skills

Required

  • Currently enrolled in a PhD program in Computer Science or a related STEM field.
  • At least 1 year of experience (coursework or project) with Machine Learning and Deep Learning.
  • At least 2 years of experience with mathematical modelling for practical problems.

Nice to have

  • Experience in deep learning foundations, including theories, models, and algorithms.
  • Experience with sequence modeling, Large Language Models (LLM), multimodal intelligence, Large Multimodal Models (LMM), and their applications to natural language processing and computer vision tasks.
  • Experience with neuro-symbolic reasoning and neural program synthesis.

What the JD emphasized

  • PhD program
  • Machine Learning
  • Deep Learning
  • mathematical modelling

Other signals

  • cutting-edge research
  • publish your results
  • deep learning foundations
  • sequence modeling
  • Large Language Models (LLM)
  • multimodal intelligence
  • Large Multimodal Models (LMM)
  • neuro-symbolic reasoning
  • neural program synthesis