Preferred Networks (PFN) will be organizing an AI residency program in Tokyo for students from outside of Japan in 2018-2019.
We are a growing startup with about 120 members based in Tokyo, Japan, focusing on applying deep learning to industrial problems such as autonomous driving, manufacturing, and bio-healthcare. We are actively developing the deep learning framework Chainer.
We are looking for brilliant students who have expertise in various topics, such as deep learning, reinforcement learning, computer vision, bioinformatics, natural language processing, distributed computing, simulation, etc.
In previous years, by selecting highly capable interns and encouraging them to tackle challenging and important problems, some of our interns were able to have their work published at top conferences such as ICML, ICCV, ICRA, and ICLR.
This year, we would like to expand our reach to attract talented students around the world and collaborate with them to tackle challenging problems in AI for a longer period, by introducing this AI residency program.
During the residency program, you will have a unique opportunity to collaborate with our excellent research team members at PFN and work on real-world applications of deep learning, while living in Tokyo; one of the most attractive cities in the world.
We are looking forward to receiving your applications! Please see below for the instructions.
●Target of this program
- Students outside of Japan
●Work time & Location:
- Business hours:
8 hours/day, 5 days/week (excluding national holidays)
- Location: Center of Tokyo
Preferred Networks Tokyo office: Otemachi Bldg. 2F, 1-6-1, Otemachi, Chiyoda-ku, Tokyo, Japan 100-0004
●Period & Compensation:
- The period of the residency program can be flexibly arranged between September 2018 and August 2019, the minimum term is 6 months
- AI residency program students are paid a competitive salary
- We will cover residence and travel cost
- We can only accept Ph.D. students or new graduates who have been accepted for Ph.D. program starting 2018 Fall
- Applicants are responsible for negotiating with their university for one year leave or deferring the admission to next year
- Experience in at least one of the technology areas (listed below) other than only attending lectures
e.g., published a paper, won a competition, part-time work, open source contribution
- Strong programming skill (any programming language)
- Fluent in either English or Japanese
- Able to work fulltime on weekdays at our Tokyo office during the period
●Preferred experience & skills:
- Machine learning and deep learning
- Experience with NumPy / SciPy / deep learning frameworks
- Experience with software & service development
- Experience working with shared codebases (e.g. GitHub / bitbucket / etc)
- Contribution to open source projects
●Candidate themes (subject to change)
1. Technology areas: Sub-field of machine learning, such as
a. Deep learning theory
b. Reinforcement learning
c. Computer vision
d. Natural language processing
e. Parallel / distributed computing
2. Application areas: Advanced applications, such as
a. Object detection / tracking / segmentation from image / video
b. Robotics / factory automation / predictive maintenance
c. Life science / healthcare / medicine
d. Human machine interaction
e. Design / content creation / visualization
f. Deep learning software (Chainer, CuPy, ChainerMN/CV/RL, etc)
g. Optimization for deep learning hardware
- Resume / CV (PDF format only. Please DO NOT include any personal or private information [e.g., age, race, nationality, religion, personal address, phone number] except name, email address, affiliation)
- Github account (optional)
●How to apply:
- Please fill the google forms and submit
Due: March 20th, 11:59 pm Tuesday (PDT)
- No late submission will be accepted
- The review process takes about 6-8 weeks after submission
- Usually, getting a visa for working in Japan takes up to 3 months
- Document review
- One-way video interview (webcam, recording)
- Skype interview in English or Japanese (multiple times if necessary)
If you have questions, please contact us at email@example.com (Sorry but no late application is accepted for fairness)