Funding

Self Funded · Partial / Stipend

Program dates

Mar 1, 2027 – Mar 12, 2027

Summer School•Japan · Onna

Machine Learning Summer School 2027 (MLSS Okinawa)

Okinawa Institute of Science and Technology (OIST)

Application Deadline

September 30, 2026

Official Page

The Machine Learning Summer School (MLSS) 2027 is hosted by the Okinawa Institute of Science and Technology (OIST) in Onna Village, Okinawa, Japan, running 1–12 March 2027. It is the successor to MLSS Okinawa 2024 and part of the long-running international MLSS series. The program selects roughly 200 participants — primarily master’s and PhD students with a strong technical background in machine learning — for two weeks of lectures, tutorials, and poster sessions covering learning theory, language models, optimal transport, diffusion models, kernel methods, computer vision, and more. Fourteen confirmed speakers include Shai Ben-David, Danqi Chen, Marco Cuturi, Arnaud Doucet, Arthur Gretton, Taiji Suzuki, and Masashi Sugiyama.

Benefits & funding

  • Two weeks of teaching from an international faculty of leading ML researchers, plus poster sessions to present your own work.
  • Accommodation is provided in-kind by the organizers (not a cash grant); shuttle buses run on weekdays between selected hotels and the OIST campus.
  • No application fee. A registration fee applies once accepted, with three tiers — students (master’s & PhD), academics (postdocs, staff scientists & faculty), and professionals (industry & non-academic). Exact amounts are listed as to-be-decided on the official application page.
  • Travel to and from Okinawa is the participant’s own responsibility; no scholarships, travel grants, or fee waivers are advertised. Industry participants may attend via company sponsorship.

Eligibility

  • Open to applicants of any nationality; visa guidance is provided for international attendees.
  • Primary audience: master’s and PhD students with a strong technical background in machine learning.
  • A limited number of places for postdocs, faculty, industry practitioners, and outstanding undergraduate students, subject to availability.
  • Applicants must have experience programming in Python, a strong interest in machine learning, and a basic understanding of linear algebra, calculus, probability, and statistics.

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  • Education required

    Bachelor Enrolled · Master Enrolled · PhD Enrolled · PhD

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Application process

  1. 1
    Apply through OpenReview (OIST.jp/2027/MLSS_Okinawa) once applications open on 1 August 2026.
  2. 2
    Submit a poster abstract and a statement of motivation by the 30 September 2026 deadline.
  3. 3
    Upload your CV and (for students) a letter of recommendation by 10 October 2026.
  4. 4
    Receive the acceptance decision by 1 November 2026.
  5. 5
    If accepted, complete registration (opens 10 November 2026) and pay the registration fee by 30 November 2026.

Program timeline

  1. Applications open on OpenReview

    1 August 2026

  2. Application deadline (poster abstract & motivation)

    30 September 2026

  3. CV and references due

    10 October 2026

  4. Acceptance notification

    1 November 2026

  5. Registration opens

    10 November 2026

  6. Registration payment deadline

    30 November 2026

  7. Summer school held at OIST, Okinawa

    1–12 March 2027