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Postdoctoral Associate
  • Job Number: 21542
  • Functional Area: Research - Scientific
  • Department: Comp Sci & Artificial Intelligence Lab
  • School Area: Schwarzman College of Computing
  • Employment Type: Full-Time
  • Employment Category: Exempt
  • Visa Sponsorship Available: Yes
  • Schedule:

Job Description

POSTDOCTORAL ASSOCIATE, Computer Science and Artificial Intelligence Laboratory (CSAIL), to join the Algorithmic Alignment Group.  Will work alongside collaborators at DeepMind and the Cooperative AI Foundation to lead the design and implementation of a large-scale Cooperative AI contest to take place next year at a major AI conference. The work is expected to be highly important and influential for driving progress in the field.  The postdoc will lead innovative research on these problems, specifically through the lens of multi-agent reinforcement learning. Specific goals of the research include the design and launch of a contest to standardize approaches and infrastructure for cooperation research; leading novel research on the incentives for cooperative behaviors; and leading a contest summary paper, along with the participants and senior advisors, to distill what was learned about the relative strengths and weaknesses of different approaches to Cooperative AI. 

A full job description is available here.  

Job Requirements

REQUIRED:  Ph.D. in computer science or other scientific or engineering field with a  focus on computation, familiarly with open-source philosophy and methodologies, broad technical knowledge of a wide variety of current artificial intelligence (AI) and machine learning (ML) research and practice, technical experience with the implementation of AI or ML tools/models/artifacts, and excellent software engineering and communication skills in academic research settings. PREFERRED:  experience with PyTorch or other ML libraries, demonstrated success at publishing in AI/ML venues, technical expertise in large-scale reinforcement learning methods and in multi-agent learning and/or game theory, and an interest in doing novel research on cooperation and multi-agent reinforcement learning.  Job #21542