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Meta Research Scientist, Human inspired AI in Paris, France

Summary:

Meta is seeking Research Scientists to join its Fundamental AI Research (FAIR) organization, focused on making significant advances in Human inspired AI. This covers the development of benchmarks and tasks that directly compare humans and machines on high level tasks (reasoning, learning, world modeling), and the design of algorithms that learn like humans do (from sparse, unlabeled and noisy data). We publish groundbreaking papers and release frameworks/libraries that are widely used in the open-source community fostering the advancement of AI at its intersection with the study of natural intelligence. We are seeking researchers with a mixed expertise in machine learning and cognitive, developmental or language science to join our research team to foster cutting-edge research in human inspired AI.

Required Skills:

Research Scientist, Human inspired AI Responsibilities:

  1. Lead research to advance the science and technology of intelligent machines.

  2. Publishing state-of-the-art research papers in both high impact machine learning and cognitive science outlets.

  3. Conducting independent research that investigates how AI can improve the science of learning in biological organisms and vice versa.

  4. Work towards long-term ambitious research goals, while identifying intermediate milestones.

  5. Lead and collaborate on research projects within a globally based team.

  6. Open sourcing high quality code and reproducible results for the community.

Minimum Qualifications:

Minimum Qualifications:

  1. Currently has, or is in the process of obtaining, a PhD in mathematics, statistics, computer science, cognitive or language science with a strong background in both theoretical and empirical disciplines.

  2. Deep interest in cross-disciplinary communication towards conducting research in human inspired AI.

  3. Experience with scalable machine learning systems, resource-efficient AI data and algorithm scaling, or neural network architectures.

  4. Experience communicating complex research for public audiences of peers.

  5. Experience with deep learning frameworks such as Pytorch, Jax, or Tensorflow.

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

Preferred Qualifications:

Preferred Qualifications:

  1. Proven track record of achieving significant results as demonstrated by grants, or fellowships, as well as publications in *ACL, top speech and language conferences and/or top cognitive (neuro)science journals.

  2. Demonstrated research and software engineering experience via an internship, work experience, coding competitions, or widely used contributions in open source repositories (e.g. GitHub).

  3. Experience solving analytical problems using quantitative approaches.

  4. Experience manipulating and analyzing complex, large scale, high-dimensionality data from varying sources.

  5. Experience in utilizing theoretical and empirical research to solve problems.

  6. Experience doing optimization based on machine learning and/or deep learning methods.

  7. Experience solving complex problems and comparing alternative solutions, tradeoffs, and diverse points of view to determine a path forward.

  8. Experience working and communicating cross functionally in a team environment.

Industry: Internet

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