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Meta is seeking a Postdoctoral Researcher to join Fundamental AI Research (FAIR), a research organization focused on making fundamental progress in AI. Individuals in this role are expected to conduct cutting-edge research in areas such as artificial intelligence, machine learning, computational statistics, and applied mathematics, particularly including topics such as deep learning, computer perception, natural language processing, representation learning, optimization, reinforcement learning, privacy in machine learning, security of AI systems, foundations of generative modeling, compression and information theory, and social implications of AI. The ideal candidate will have a keen interest in producing new science to understand intelligence and technology towards achieving advanced machine intelligence
Job Responsibility:
Directly contribute to experiments, including designing experimental details, writing reusable code, running evaluations, and organizing results
Work with a large team
Help identify long-term ambitious research goals as well as intermediate milestones
Prioritize research that can be applied to Meta's product development
Mentor other team members
Play a significant role in healthy cross-functional collaboration
Requirements:
Currently has, or is in the process of obtaining a Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
Currently has or is in the process of obtaining a PhD degree in Computer Science or a similar field
Research background in machine learning, natural language processing, computer vision, computational statistics, applied mathematics, or related areas
Track record of recent and consistent publications reflecting expertise in theoretical and/or empirical research
Experience solving analytical problems using analytic and quantitative approaches
Must obtain work authorization in country of employment at the time of hire and maintain ongoing work authorization during employment
Nice to have:
First-authored publications at peer-reviewed conferences (ICML, ICLR, NeurIPS, CVPR, ECCV, ICCV, ACL, NAACL, EMNLP, or similar)
Experience communicating research for public audiences of peers
Experience working and communicating cross functionally in a team environment
Experience solving complex problems and comparing alternative solutions, trade-offs, and different perspectives to determine a path forward
Research and engineering experience demonstrated via grants, fellowships, patents, internships, work experience, and/or coding competitions