Researchers in Machine Learning and Data Science Unit

The Okinawa Institute of Science and Technology Graduate University (OIST; see is a dynamic new graduate university of science and technology in Okinawa Prefecture, Japan. The university is located on 85 hectares of protected forestland overlooking beautiful shoreline and coral reefs. The campus is striking architecturally, and the facilities are outstanding (OIST campus video tour). There are no academic departments, which facilitates multidisciplinary research. Outstanding resources and equipment are provided and managed to encourage easy access and collaboration. English is the official language of the University, and the university research community is fully international, with more than 50 countries represented. OIST is rapidly gaining recognition in the worldwide academic community as a model for excellence in education and research.

Position summary:

We focus on developing machine learning algorithms and accelerating scientific discovery using machine learning. More specifically, we are working on deep learning models for small sample data, distributed/federated learning, graph neural networks, and optimal transport methods. Moreover, with collaborators, we are working on finding new therapeutic targets for Acute Myeloid Leukemia (AML) using machine learning methods.


1919‐1 Tancha, Onna‐son, Okinawa, Japan 904-0495


  1. Develop machine learning models for high-dimensional, real-world applications.
  2. Pursue your own scientific interests in a highly collaborative environment.
  3. Write research papers and develop software in Python.
  4. (For staff scientist applicants) Mentor younger scientists.



  1. PhD in Computer Science, a related technical field
  2. Experience in Machine Learning, computer vision, and natural language processing, or related fields.
  3. Programming knowledge (e.g., Python or C++)
  4. (For staff scientist applicants) Strong research background and publications in top tier computer science conference including ICML, NeurIPS, AISTATS, ICLR, CVPR, ECCV, ACL, EMNLP etc.


  1. Strong research background and publications in top tier computer science conference including ICML, NeurIPS, AISTATS, ICLR, CVPR, ECCV, ACL, EMNLP etc.
  2. Ability to design new research problems.
  3. Experience in collaboration with non-machine learning experts.

Report to 

Associate Professor Makoto Yamada, Machine Learning and Data Science Unit

Starting Date 

As early as possible, or negotiable

Term & Working Hours 

Full-time, the position is initially for three years and can be extended to 2 more years based on performance and mutual agreement.

Compensation & Benefits 

Compensation in accordance with the OIST Employee Compensation Regulations


  • Relocation, housing and commuting allowances
  • Annual paid leave and summer holidays
  • Health insurance (Private School Mutual Aid )
  • Welfare pension insurance (kousei-nenkin)
  • Worker’s accident compensation insurance (roudousha-saigai-hoshou-hoken)

How To Apply 

Apply by uploading your Submission Documents to here.

Submission Documents 

  • Cover letter
  • CV including the publication list
  • Summary of research experience and research plan (2-4 pages)
  • Names of 2 potential reference writers

* Prior to the start of employment all new hires are required to successfully complete a background check. Personal information including employment history and academic background should be submitted to third-party administrators after a conditional offer of employment.

Application Due Date 

Applications deadline will continue until the position is filled. (Applications will be screened upon arrival)


  • OIST Graduate University is an equal opportunity, affirmative action educator and employer and is committed to increasing the diversity of its faculty, students and staff. The University strongly encourages applications from underrepresented groups.
  • Information provided by applicants or references will be kept confidential, documents will not be returned. All applicants will be notified regarding the status of their applications.
  • Please view OIST policy for rules on external professional activities
  • Further details about the University can be viewed on the OIST website

Job Description PDF