Research Intern - ML and Computational Biology for the Immune System

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

Research Intern position at Microsoft Health Futures focusing on applying ML and statistical modeling to understand the human immune system for precision medicine. The role involves building large-scale models of immune responses and immune cells, integrating techniques like representation learning, causal inference, and generative modeling with biological insights.

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

  • PhD program in Machine Learning, Statistics, Computer Science, Computational Biology or other related field.

Nice to have

  • Ability to develop original research agendas demonstrated by a publication record as a lead author.
  • Skills analyzing large datasets including but not limited to large-scale learning, experimental design, and statistical modeling.
  • Able to collaborate and communicate across disciplines as part of a cross-functional team.
  • Experience working with complex biological datasets.

What the JD emphasized

  • Accepted or currently enrolled in a PhD program in Machine Learning, Statistics, Computer Science, Computational Biology or other related field.
  • Ability to develop original research agendas demonstrated by a publication record as a lead author.

Other signals

  • integrating statistical modeling and machine learning (ML) techniques
  • representation learning
  • causal inference
  • generative modeling
  • large-scale models of immune responses and immune cells