Special Grant Program for International Students (April 2026)

Special Grant Program for International Students / Research Assistant Program of Graduate School of Environmental Science (April 2026)

This program will select students who can likely contribute internationally in their research field, from those applying to doctoral courses at the Graduate School of Environmental Science.
Participating in research as a Research Assistant (RA) is very meaningful to develop your research ability. Each Research Assistant must serve to achieve the objective of a research subject directed by a Graduate School of Environmental Science faculty member. The research subjects are listed below.

Period

Maximum 3 years, with the annual extension subject to evaluation of achievements by a faculty committee.

Qualifications of application (Eligibility):

Students (mainly from developing countries) who seek admission to the doctor courses of the Graduate School of Environmental Science.
〈Notes〉
If the students of this Special Grant Program are also selected as recipients of the doctoral fellowships, they must choose one of them and decline the others.

Payment Exemption / RA Allowance:

Payment Exemption: Total amount of school fees is entirely covered by Hokkaido University (i.e., entrance exam fee of 30,000 yen, admission fee of 282,000 yen, and the annual tuition fee of 535,800 yen for each of three years). RA Allowance (depending on the actual working time): Total 3 million yen (1 million yen annually for three years)
The applicant should meet travel expenses for the entrance exam.

Application Deadline

10 December (Wednesday) 2025

Application for the program:

Applicants are required to submit the documents listed below via email. The documents should not be written in a language other than English.

1. Curriculum vitae with the applicant’s photograph
2. Academic transcripts
3. Graduation certificate
4. A list of publications and presentations in scientific meetings
5. A research proposal
6. Direction and comments of potential supervisor and at least one co-supervisor, including proofs of communication between you and the potential supervisors
7. Master’s thesis or other documents in proof of your research ability

Reference and address to apply

Academic Affairs Section
Graduate School of Environmental Science, Hokkaido University
E-mail: kyomu (at) ees.hokudai.ac.jp

List of possible research subjects (April 2026)

Title: Removal of Greenhouse Gases and Water Pollutants Using Porous Materials
Professor: Shin-ichiro Noro

Limiting global warming is essential to the realization of a sustainable society. Greenhouse gas separation technologies are among the most promising methods for preventing global warming. On the other hand, the separation and removal of water pollutants are critical for ensuring safe and sustainable water resources. This research aims to develop porous materials showing efficient removal of greenhouse gases such as carbon dioxide, methane, and nitrous oxide, and water pollutants such as heavy metal cations, per- and polyfluoroalkyl substances, and pesticides, and understand removal mechanisms. A successful candidate is required to have knowledge of synthetic chemistry, porous materials, and fundamentals of adsorption/desorption and have experience in the synthesis of porous materials.

Title:  Multi-Sensor Geospatial Data for Environmental Monitoring and Natural Resource Management
Associate Professor: Ram Avtar

Rapid population growth, industrialisation, and societal change are intensifying pressure on natural resources, accelerating depletion and ecosystem degradation. Effective stewardship requires timely, reliable monitoring and data-driven assessment to inform policy and management.
Advances in multi-sensor remote sensing—including optical, SAR, LiDAR, hyperspectral, and UAV platforms enable precise detection of land-use/ land-cover change, deforestation, forest degradation and other landscape dynamics. When integrated with in-situ observations and advanced machine -learning methods, these data deliver actionable indicators for sustainable resource management.
This study aims to use multi-sensor geospatial and in-situ data, to develop a comprehensive framework for monitoring natural resources. A special emphasis is placed on semi-automated workflows and data- intensive pipelines (from ingestion to analytics to visualisation) for operational management of resources. The ideal candidate should possess strong expertise in geospatial technologies, and environmental data analysis using ML/AI (eg. Python/R/GEE) to contribute meaningfully to cutting-edge research in natural resource management.