Application Deadline: January 13, 2017
The residency program is similar to spending a year in a Master’s or Ph.D. program in deep learning. Residents are expected to read papers, work on research projects, and publish their work in top tier venues. By the end of the program, residents are expected to gain significant research experience in deep learning.
The environment in the Google Brain Team is uniquely conducive to outstanding deep learning research: world-class large-scale infrastructure for training deep neural networks, large data sets in a wide variety of domains, and a high concentration of strong deep learning scientists. It is an environment where pure research and important applications reinforce and support each other in a virtuous cycle. To get a taste for their work, please see the Google Brain publications list.
The Google Brain Residency Program is based in Mountain View, California and residents are expected to work on-site.
- Google is accepting applications until January 13, 2017
- Interviews (phone, video, and/or on-site in Mountain View) will primarily take place from February to March 201
- Application results will be finalized by April 2017
- The program starts in July 2017 and runs for 12 months
Application Details: Candidates will be asked to provide the following information with their applications. If you’d like to submit additional materials after applying, please do so at the following link: https://services.google.com/fb/forms/brainresidency/. We recommend gathering these materials in advance as this will greatly help you with your application.
- Current CV
- Cover letter including a statement on why you think you’d be great for the Google Brain Residency Program
- Transcripts from your most recent degree
- Letter of recommendation (minimum of one letter) – Letters may be sent directly to email@example.com
- Links to GitHub, papers and/or blogs if applicable
- Understand a large body of research in deep learning quickly.
- Work with your research mentors to formulate research project(s) and/or novel application(s) of the technology.
- Conduct research and publish it in competitive venues.
- Implement algorithms in TensorFlow.
- BS degree or equivalent practical experience in a STEM field such as Computer Science, Mathematics, or Statistics.
- Completed coursework in calculus, linear algebra, and probability, or their equivalent.
- Experience coding in C/C++ and/or Python.
- Eligible to work in the United States.
- MS degree or Ph.D in relevant fields and/or post graduate or industry experience.
- Research experience in Machine Learning and Neural Networks (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.
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