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Research Intern - Advancing Scientific Discovery using Large Language Models

Applications are closed

  • Internship
    Full-time
    Off-cycle Internship
  • Software Engineering
  • Redmond

Requirements

  • Required Qualifications:
  • Currently enrolled in a graduate program in Computer Science or a related engineering field
  • 1+ years experience working in Python
  • Other Requirements:
  • Research Interns are expected to be physically located in their manager’s Microsoft worksite location for the duration of their internship.
  • In addition to the qualifications below, you’ll need to submit a minimum of two reference letters for this position. After you submit your application, a request for letters may be sent to your list of references on your behalf. Note that reference letters cannot be requested until after you have submitted your application, and furthermore, that they might not be automatically requested for all candidates. You may wish to alert your letter writers in advance, so they will be ready to submit your letter.
  • Preferred Qualifications:
  • Experience in working with GPT4 and beyond
  • Have built apps or experiences that leverage natural language processing, data science, and machine learning
  • Ability to move fast and being a self-starter

Responsibilities

  • As a Research Intern, working across a multi-disciplinary team you will have the opportunity to shape the direction of your research project based on the areas that excite you most. The list below is illustrative of the many opportunities for impact you could be a part of.
  • Utilizing LLMs to analyze vast amounts of scientific research
  • Devising techniques to identify gaps in current scientific knowledge
  • Leveraging literature to propose new hypothesis/techniques for addressing current gaps
  • Creating personalized knowledge dashboards to help researchers stay updated in their fields, enabling efficient navigation through extensive research data.
  • Build a personalized research copilot that helps researchers worldwide accelerate their productivity and findings
  • Design an approach to augment experimentation capabilities by helping researchers rule out ideas quickly using scientific knowledge
  • Collaborate and partner with other teams working across Microsoft to explore different approaches to the scientific discovery problem (E.g., Material Sciences, Chemistry, Health Futures etc.)

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