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.
* 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.
* 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.
* 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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