Facebook 2021 AI Research (FAIR) Residency Program

Facebook 2021 AI Research (FAIR) Residency Program

The  Facebook AI Research (FAIR) Residency Program is seeking applications from people who have a strong technical background and are passionate about AI research.

The Facebook AI Research (FAIR) Residency Program is a one-year research training program with Facebook’s AI Research group, designed to give you hands-on experience of machine learning research. The program will pair you with a senior researcher or engineer in FAIR, who will act as your mentor. Together, you will pick a research problem of mutual interest and then devise new deep learning techniques to solve it. We also encourage collaborations beyond the assigned mentor. The research will be communicated to the academic community by submitting papers to top academic venues (NIPS, ICML, ICLR, CVPR, ICCV, ACL, EMNLP etc.), as well as open-source code releases. Visit the FAIR research page for examples of research performed in FAIR .

The AI research residency experience is designed to prepare you for graduate programs in machine learning, or to kickstart a research career in the field. This is a full-time program that cannot be undertaken in conjunction with university study or a full-time job.

Aim and Benefits of Facebook AI Research Internships

Residents will be paid a competitive salary. Residents will also:

1. Learn how to perform research in deep learning and AI.
2. Understand prior work and existing literature.
3. Work with research mentor(s) to identify problem(s) of interest and develop novel AI techniques.
4. Translate ideas into practical code (in frameworks such as PyTorch, Caffe 2).
5. Write up research results in the form of an academic paper and submit to a top conference in the relevant area.

Duration of Program: 

1. Residency Program start: August 2021
2. Residency Program end: August 2022

Requirements for Facebook AI Research Internships Qualification

Prior experience in machine learning is certainly a strength but we seek people from a diverse range of backgrounds, including areas ostensibly unrelated to machine learning such as (but not limited to) math, physics, finance, economics, linguistics, computational social science, and bioinformatics.

1. Bachelors degree in a STEM field such as Mathematics, Statistics, Physics, Electrical Engineering, Computer Science, or equivalent practical experience.
2. Completed coursework in: Linear Algebra, Probability, Calculus, or equivalent.
3. Coding experience in a general-purpose programming language, such as Python or C/C++.
4. Familiarity with a deep learning platform such as PyTorch, Caffe, Theano, or TensorFlow.
5. Ability to communicate complex research in a clear, precise, and actionable manner.

Preferred Qualifications

1. Research experience in machine learning or AI (as established for instance via publications and/or code releases).
2. Significant contributions to open-source projects, demonstrating strong math, engineering, statistics, or machine learning skills.
3. A strong track record of scholastic excellence.

Application Deadline

The deadline is January 31, 2021

How to Apply