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AI Research Scientist Intern (PhD)

  • CDD
  • Paris
  • Publié il y a 2 ans
  • Les candidatures sont actuellement fermées.

Facebook

Meta is seeking Research Interns to join our Natural Language Processing teams. These teams are part of the Facebook AI Research (FAIR) organization within Meta, working to accelerate science, by leveraging state-of-the-art NLP and Language Modeling at scale. The opportunities and challenges of this work are immense as it can have a direct impact on the accessibility and practice of science, at scale. Our research spans multiple areas across NLP and machine learning, including deep learning, language modeling, natural language understanding and generation, self-supervision, question answering & reasoning (STEM), information retrieval, factual consistency and continual learning.As a Research Intern, you will help us apply cutting-edge NLP algorithms to a wide range of media understanding challenges at Meta AI. Our team at Meta AI offers 2023 internship opportunities with start dates from July to October. To learn more about our research, visit https://research.facebook.com.

AI Research Scientist Intern (PhD) Responsibilities:

  • Perform research to advance Language Models technology

Minimum Qualifications:

  • Currently has, or is in the process of obtaining a PhD degree (or equivalent) in the field of Machine Learning, Artificial Intelligence, Natural Language Processing or similar
  • Experience in Python
  • Research and/or work experience in machine learning, deep learning, and/or Natural Language Processing
  • Experienced with training and/or playing with Large Language Models

Preferred Qualifications:

  • Proven track record of achieving results as demonstrated by grants, fellowships, patents, as well as first-authored publications at workshops or conferences such as ACL, EMNLP, NAACL, AAAI, ICML, NeurIPS, ICLR or similar
  • A strong interest in theoretical and empirical research and for answering hard questions with research
  • Interpersonal experience: cross-group and cross-culture collaboration
  • Experienced with the development of enterprise-level AI, machine learning and deep learning systems, involving big data management and GPU compute

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