Fully Funded Research Fellowship for PhD Students Provided by Facebook

The Facebook Fellowship Program is now open to students in any year of their PhD study. The program is designed to encourage and support promising doctoral students who are engaged in innovative and relevant research in areas related to computer science and engineering at an accredited university. People of diverse backgrounds and experiences, especially those from traditionally underrepresented minority groups are encouraged to apply. Winners of the Fellowship are entitled to receive two years of tuition and fees paid, a stipend of $37,000 each year and up to $5,000 in conference travel support.

Eligibility Criteria:

1. Applicants must be full-time PhD students currently involved in on-going research who are enrolled in an accredited university in any country.
2. Students' work must be related to one or more relevant disciplines (see research areas below).
3. Students must be enrolled during the academic year(s) the Fellowship is awarded.
4. Students should not apply for Facebook Fellowships if they are actively being funded by Facebook through some other sponsorship or collaboration and/or if they are actively being supervised (or co-supervised) by a Facebook researcher. If in doubt, please email academicrelations@fb.com.

Awards:

1. Tuition and fees paid for the academic year (up to two years/four semesters).
2. $37,000 grant (one-time payment during each academic year).
3. Up to $5,000 in conference travel support.
4. Paid visit to Facebook headquarters to for the annual Fellowship Summit.

Research Areas:

1. Applied Statistics.
2. AR/VR Photonics and Optics.
3. AR/VR Privacy and Ethics.
4. Blockchain and Cryptocurrency.
5. Computational Social Science.
6. Computer Graphics.
7. Computer Vision.
8. Compute Storage and Efficiency.
9. Distributed Systems.
10. Economics and Computation.
11. Instagram/Facebook App Well-being and Safety.
12. Machine Learning.
13. Natural Language Processing.
14. Networking and Connectivity.
15. Privacy and Data Use.
16. Programming Languages.
17. Security/Privacy.
18. Social and Economic Policy.
19. Spoken Language Processing and Audio Classification.
20. Structured Data Stores.
21. Systems for Machine Learning.

For more information about the previous fields, click here.

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