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The goal of this fellowship is to support and encourage Ph.D. candidates to generate groundbreaking research publications, open source contributions, and/or other forms of research dissemination. Bloomberg fellows are supported both financially (tuition support and a $42,000 stipend) and through mentorship, career counseling, and research internships.

Research Topics

Topics of interest include, but are not limited to:

  • AI Safety
  • Controllable Summarization
  • Conversational Search Systems
  • Domain Adaptation of pretrained models
  • Evaluation of generative models
  • Generative Information Retrieval
  • LLMs for planning and reasoning
  • Multimodal models for document understanding
  • Neural semantic parsing
  • Retrieval augmented generation
  • Reward modeling and alignment
  • Scalable and efficient LLM inference
  • Time-series modeling

Eligibility

  • Applicants must be full-time doctoral students during the next academic year.
  • Recipients must complete a 14-week summer internship in New York or London for each year of their fellowship. This is a paid research internship and the project will be research-focused.
  • Recipients may not be supported by any other industry fellowships for the duration of the Bloomberg fellowship. Non-industry funding may be permitted on a case-by-case basis.

Fellowship Website:

https://www.bloomberg.com/company/values/tech-at-bloomberg/data-science/academic-engagement-programs/data-science-ph-d-fellowship/#introduction

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