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Postdoctoral Researcher (AI) - Self-Supervised Learning
Facebook in New York, New York
 
 
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Date Posted 04/02/2019
Category
Postdoctoral-Computer Science
Employment Type Fulltime
Application Deadline Open until filled
 
 
 
 
 

Facebook's mission is to give people the power to build community and bring the world closer together. Through our family of apps and services, we're building a different kind of company that connects billions of people around the world, gives them ways to share what matters most to them, and helps bring people closer together. Whether we're creating new products or helping a small business expand its reach, people at Facebook are builders at heart. Our global teams are constantly iterating, solving problems, and working together to empower people around the world to build community and connect in meaningful ways. Together, we can help people build stronger communities — we're just getting started.

Facebook is seeking two postdoctoral researchers to join Facebook AI Research (FAIR), a research organization focused on making significant progress in AI. The ideal candidate will have a keen interest in pursuing research in self-supervised learning, a paradigm for machines to pre-learn abstract, hierarchical representations of the world that would enable them to learn any complex tasks with very few labeled samples or few interactions. They will join a research group that is developing a general formulation of SSL applicable to a wide range of domains. This is an exciting opportunity to join a growing area of research within FAIR. 
Term length would be 12 to 18 months. To learn more about our research visit https://research.facebook.com.

RESPONSIBILITIES

  •  

    Collaborate on research to advance the science and technology of self-supervised learning.

  •  

    Collaborate on research that enables learning abstract, hierarchical representations and background knowledge from data (images, video, text, audio, and other modalities).

  •  

    Influence progress of relevant research communities by producing publications.

  •  

    Collaborate and increase productivity on existing FAIR projects as a contributing team member.

 

MINIMUM QUALIFICATIONS

  •  

    Currently has or is in the process of obtaining a PhD degree in AI, Machine Learning, Computer Science, Data Science, Applied Mathematics, Electrical Engineering, Physics or related field or related experience.

  •  

    Track record of publications that demonstrate experience in Deep Learning.

  •  

    Experience collaborating within a team to solve analytical problems using quantitative approaches.

  •  

    Experience manipulating and analyzing data from varying sources.

  •  

    Experience communicating research for public audiences of peers.

  •  

    Knowledge in one or more programming languages.

  •  

    Must obtain work authorization in country of employment at the time of hire, and maintain ongoing work authorization during employment.

 

PREFERRED QUALIFICATIONS

  •  

    First-author publications at peer-reviewed conferences with ML/DL content (e.g. NeurIPS, ICML, ICLR, CVPR, ICCV, ECCV, ACL, NACL, and EMNLP).

  •  

    Experience conducting original research that can be applied to deep learning research at FAIR (e.g. physics, mathematics, robotics).

  •  

    Experience with PyTorch or similar frameworks.

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