Google AI Resident Program 2018
The Google AI Residency Program (formerly known as the Google Brain Residency Program) is a 12-month role designed to advance your career in machine learning research. Residents will work alongside distinguished scientists from various Research teams. The goal of the residency is to help residents become productive and successful AI researchers.
We created the Google Brain Residency Program in 2015, and we are now expanding it into a broader program that involves not just the Google Brain team, but a broader group of research teams doing machine learning research. Residents will have the opportunity to do everything from conducting fundamental research to contributing to products and services used by millions of people. We encourage our Residents to publish their work externally. Take a look at what some have done in previous years.
We are looking for people who want to learn to conduct machine learning research in collaboration with our researchers. You may have research experience in another field (e.g., mathematics, physics, bioinformatics, etc.) and want to apply machine learning to this area, or you may have limited research experience but, a desire to do more. Of course having machine learning research experience is great.
Current students will need to graduate from their current degree program before the residency begins. We encourage candidates from all over the world to apply. If a candidate requires a work visa, Google will explore what options are available on a case by case basis.
The Google AI Residency Program is primarily based in the Bay Area and is expanding to new locations in 2018. Depending on resident interests, project fit, and team needs, accepted residents may be based in locations outside of the Bay Area, including New York; Cambridge (Massachusetts); Montreal; and Toronto. Residents are expected to work on site.
To apply, please read all instructions below and submit the following required materials:
- Cover Letter
Your application should show evidence of proficiency in programming and in prerequisite courses, notable performance in competitions, or links to an open-source project that demonstrates programming and mathematical ability. Your application should present a interest in the field. This can be demonstrated through links to publications and blog posts, or implementations of one or more (even slightly) learning algorithms, including an explanation for what makes it novel.
- BA/BS degree in a STEM field such as Computer Science, Mathematics or Statistics, or equivalent practical experience.
- Completed coursework in calculus, linear algebra, and probability, or their equivalent.
- Experience with one or more general purpose programming languages, including but not limited to: C/C++ or Python
- Experience with machine learning or deep learning, applications of machine learning to NLP, computer vision, speech, systems, robotics, algorithms, optimization, on-device learning, social networks, economics, information retrieval, journalism, or health care.
- Research experience in machine learning or deep learning (e.g., links to open-source work or link to novel learning algorithms).
- Strong open-source project experience that demonstrates programming, mathematical, and machine learning abilities and interest.
- We are accepting applications until January 8th, 2018.
- Interviews (phone, video, and/or on-site) will primarily take place from mid-January to March 2018.
- Application results will be finalized by end of March 2018.
- The program will start in summer 2018 and run for 12 months.
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