• Home
  • News
  • PFN & PFI Summer Internship Program

News

PFN & PFI Summer Internship Program

2016.04.13

As goes the tradition, Preferred Infrastructure (PFI) and Preferred Networks (PFN) will be organizing the joint internship program this summer too. We are looking forward to receiving students who want to join us in creating new technologies and services. Students who previously applied are also welcome to try again this year.

Application Guideline
Qualification requirements and emplyment conditions are same as PFN and PFI, except that you must be as fluent in Japanese as natives if you want to work on PFI’s themes. To which company candidates will be assigned depends on the themes they will work on.

Period
August 1st 2016 – September 30th 2016
(The period of the internship can be flexibly arranged.)

Time & Place
8 hours/day, 5 days/week (excluding holidays)
Otemachi-Bldg. 2F 1-6-1, Otemachi, Chiyoda-ku,Tokyo, 100-1004

Salary
High school: 1200Yen/hour
Technical college/Undergraduate/Graduate: 1500Yen/hour
Transportation expenses (up to 10000Yen/month) are also covered.

Why join the PFN internship program?
・You will be collabolating and be mentored by experts in various fields including information retrieval, natural language processing, deep learning, algorithms, distributed processing, computer vision, etc.
・You will experience every aspect of a startup company. It is valuable to those who want to work in or to be a founder of startups.
・You can make public the results of your work during the internship program, as OSS or paper, etc. (Some restrictions might apply)

Qualification requirements:
We are looking for highly motivated people who have Software development capabilities. Expertise in the fields mentioned above, or prior development experience are taken into consideration, but are not a must. Application requirements are as follows:
・Currently a students 18 of age or older (High school, technical college, college, graduate students, others could also be discussed.)
・Have programming skills (regardless of the programming language)
・Able to work fulltime on weekdays at our Tokyo office
・If you want to work on PFI’s themes, you must be as fluent in Japanese as natives (fluency in English and Chinese are welcome).
# We will prepare accommodation for those who live far from Tokyo.
# Women and Non-Japanese speakers are also very welcome
# You can still apply even if you are not a fully-fledged application developer

How to apply:
Please send the application documents below to intern-apply@preferred.jp
Questions about the internship program are also accepted by this address.

Application documents:
・Resume (Name, address, contact information, background)
・Proof of skills; explain your strengths and expertise fields, etc. (one A4 page)
Ex: List of papers, received awards, developed/used Software&Services, programming contests participation history, personal website/blog, twitter account, etc.
・Motivation letter (Please include your interest field/theme and your expectations from the internship.)
# This is a very important for both the admission procces, and the internship theme selection, so please describe in as much detail as possible.

Application Deadline
May. 8th, 2016 (sun.) 23:59 (JST)

Selection process:
Selection process:
1. Application documents screening: Starts on May 8th. Results are announced to applicants via email in a week.
2. Pre-interview task: Applicants who passed receive a task via email.
3. Interviews: First interview starts in June (Skype is used in case of remote applicants)
4. Final results: Result of the selection processes is announced to applicants in the beginning of July.

Themes
@PFI
1.Technology field: Natural Language Processing for Japanse documents
・Automatic document classification
・Named entity recognition
・Synonym Extraction
・Automatic summarization
・Similarity search

2. Technology field: Speech Recognition for Japanese speech
・Speech recognition by deep learning.
・Document recognition by deep learning.
・Speaker identification
・Noise filtering

@PFN

Application fields
・Image recognition
・Anomaly detection
・Robotics (bipedal walking, car control)
・Genomics, Epi-genomics, proteomoics
・Art generation (Generation of images, videos, sounds etc.)
・Application of deep learning to embedded system
Stream processing for IoT

Research fields
・Machine learning with limited labels (One-shot, Weakly superivsed, Semi-supervised Learning)
・Distributed algorithm, Distributed deep learning
・Deep generative model
・Machine learning using simulators

Contact

Contact us here.