(Revised 2024/2/21)

Kobe University’s‘Next-Generation Outstanding Doctoral Human Development Project based on Cocreation in Different Fields’
Academic Year 2024 Application Instructions
About Technology Agency (JST)’s Support for Pioneering Research Initiated by the Next
Generation (SPRING) Program, Kobe University is inviting applications for this project for Kobe
University’s ‘Next-Generation Outstanding Doctoral Human Development Project based on Cocreation in Different Fields’
1. Aim:The project aims to give Kobe University doctoral students from various fields a solid
grounding in mathematics and data science. This grounding will enable them to becomeoutstanding PhD. graduates who can play an active global role in interdisciplinary fields. By
cultivating transferable skills through our education and research, we aim to produce experts
required by society.
2. Funding:Those selected by this project will receive research support funds and research grants. Inaddition, we will provide a Comprehensive Support Package for Kobe University PhD. students
to give recipients increased opportunities to improve their research skills and receive career
path support.
Funding and research grants:
Research support fund
2,200,000yen per year
Research grant
200,000yen per year ＋additional funds
・Additional funds will be provided based upon the review of the application contents and budget.
・Top-selected students may be exempted from paying tuition fees for the 2024 academic year.
3. Period:
From April 1, 2024 until course completion（However this funding will not exceed the standard
course completion period）* Depending on the enrollment period and screening results, support may start from October
1, 2024.
4. Number of Nominees
Approximately 50 students in total (A few students in grades 2-4 )*However, it is possible that the number of applicants may change in the future, or that there
will be no selectees at each grade level.
5. Eligible Graduate School:
All graduate schools at Kobe University.
6. Application Requirements:
The applicant must be fallen under all 1),2),3).
１）The applicant will be enrolled as a doctoral student at one of Kobe University’s graduate

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(Revised 2024/2/21)

schools as of AY 2024(Including prospects, 1st through 4th year students may apply.).
２）Those who are expected to complete their degree within the standard completion period.
３）The applicant should be affiliated with a laboratory that can manage the project’s budget(includes prospective laboratory).
However, students to whom the following applies at the time of application cannot apply:・Students who have exceeded the standard course completion period.
・JSPS research fellows (including prospective fellows), MEXT scholarship students (includingprospective students), and international students receiving scholarships from your homecountry.
・Kobe University doctoral student fellows.
・Students who are receiving a stable income (over 2,400,000yen per year) that meets theirliving expenses (however, those receiving an unstable income through part-time/temp
work can still apply).
7. How to Apply:１）Application Deadline：March 12 , 2024 (Tuesday) 12:00(noon)
２）Please complete Form 1 and convert it to a PDF file, and submit it using the application
form.
*The total file size must be less than 2 MB when sent.
*You can write your answers to sections 2 ~ 4 of Form 1 in English*It is preferable to inform your supervisor that you are applying.
*If you do not receive an email receipt after submission, please contact the contact person.
*If you are unable to submit an application using the application form, please contact thecontact person.
Application Form:
https://forms.gle/QFC72XPepQeVkAe7A
8. Selection Process:・Candidates will be chosen by the project’s steering committee.
・ Selections will be made by judging how well the information submitted in Form 1
corresponds to the review criteria on Sheet 2.
・Interviews will be carried out as required during the selection process.
・Selection results are due to be published on the Career Center homepage by around early
April 2024.
9. Recipient’s responsibilities
１） Submit a research progress report every year
For the year in which you complete your doctorate, you may use your degree thesis as thereport.
２）The recipients are required to actively participate in the doctoral student support package
programs (Sheet 1)and participate in the program equivalent to 2 credits of lessons (1 credit is
45 hours of study) per year. In particular, it is required that you make more than one
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(Revised 2024/2/21)

in this package may not be regular courses with credits.
３） Take the designated mathematics and data science courses (Sheet 3) during the period.
４）Registration in the dedicated matching system for the job-based research internshipprogram.
５）Actively disseminate the research results via academic papers and/or academic conference
presentations.
６）Attend events specified by the steering committee.
７）Respond to various surveys, such as follow-up survey on your career 10 years after
graduating.
*Please be aware that credit numbers and course names mentioned in this document are
subject to change.
10. Disqualification or reduction from funding
If any of the following points apply, the project may be disqualified or reduced from selection.
１）The application requirements have not been met.
２）The execution of the research plan, or the funded student’s performance of their duties isdeemed to be unsatisfactory.
３）The applicant submits a withdrawal notice.
４）The university president or the project’s steering committee determines that there is cause
for disqualification or reduction.
11. Precautions:・A final income tax return where research support funds are taxed as miscellaneous income isrequired.
・Recipients are permitted to earn remuneration from teaching assistant/part-time job positions,internships or prizes from academic societies, as long as these do not hinder their research
activities.
・Your name will be published on the University homepage if your project is selected.
12. Inquiries:
Kobe University Main Office for Doctoral Student Support TEL: 078-803-5217
Email Address：crct-hakase@edu.kobe-u.ac.jp

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(Revised 2024/2/21)（Sheet 1）‘Next-Generation Outstanding Doctoral Human Development Project based on Co-creation inDifferent Fields’Comprehensive Support Package for Kobe University PhD students
A. Global Education/Study Abroad Support Program
B. Mid- to Long-term Internship Program
C. Mathematics/Data Science Education Program
D. Cross-disciplinary Co-creation Program
E. Career Support Program for PhD
F. International Student Support Program

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(Revised 2024/2/21)（Sheet 2）‘Next-Generation Outstanding Doctoral Human Development Project based on Co-creation in
Different Fields’
Review criteria and contents
Review criteria
Research Achievements

Contents
Do the applicant’s research achievements show future
potential?

Positioning of Research

Does the applicant explain the background behind theirchosen research theme, and is the idea outstanding?

Research aim/contents

Are the research aim, methodology and contents clearlyindicated? Does the research method show originalityand does the applicant indicate how they will develop
their research topic?

Research Competency

Are the applicant’s ‘strengths in relation to research’ and‘factors considered necessary for further development’concretely explained, and are they able to sufficiently
self-analyzed their own research performance? In
addition, do they fully expect to become an outstanding
researcher who bears responsibility for the future ofacademia?

Mathematics/Data Science

Does the applicant have a strong desire to acquire data
science training?

Development into

Does the research plan or future plan contain aspects

multidisciplinary co-creationthat are expected to be developed into multidisciplinary

researchco-creation research?

Development of challenging

Does the research plan or future plan contain aspects

researchthatareexpectedtobedeveloped

into

pioneering/challenging research?
Development of new research

Is the applicant not only eager to contribute towards thefields

development of their current specialized field but also to
break into and develop new research fields?

Capacity to resolve social issues

Has the applicant paid attention to social issues? Havethey acquired the skills via their doctoral research tocontribute towards resolving these issues? How tocontribute to science, technology and innovation in Japanin the future.

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(Revised 2024/2/21)（Sheet 3）
Mathematics/Data Science Education Program
Mathematical and data science education programs must take at least 2 credits before
completion. These programs will be provided by Kobe University’s Center for Mathematicaland Data Sciences. These may not be a regular credited course depending on the graduateschool. The following programs were held on AY 2023.
Course Title
Advanced Data
Science 1
Advanced Data
Science 2

credit1

Exercise in
Practical Data
Science, A
Exercise in
Practical Data
Science, B

1

PBL Exercises in
Data Science(contest type)1

JRI-Kobe Openinnovation
Workshop Financial
Business andInformation System
Engineering
Theory of
Stochastic
Processes

1

Topics in Applied
Mathematics 3a
Topics in Applied
Mathematics 3b1

112

Contents
In Advanced Data Science 1, students learn about thetechnical aspects of artificial intelligence and machinelearning, which are the foundation of data science. In
Advanced Data Science 2, problem-solving workshops areheld on the practical applications of data science basedon case reports from companies on the user side ofartificial intelligence technology and companies thatprovide technology (companies on the seed side).
Learn data analysis methods and acquire basic knowledge
to solve problems. Also, learn how to operate the systemthrough hands-on exercises using actual data.
PBL (Project Based Learning) through group work, in whichdata that may be relevant to actual issues is provided by
the local government, with the aim of setting and solving
issues through data analysis and analysis.
Practical learning of how to handle data, classification
and regression problems using Python through PBL (ProjectBased Learning) exercises modeled after data science
competitions.
Through PBL (Project Based Learning) group work, students
will learn how the basic technologies of information
systems engineering, such as algorithms, data structures,
cyber security, information communication networks, andartificial intelligence, are used in actual financial
businesses and how they are deeply related to each other.
Students will understand the rudiments of stochastic
analysis based on Brownian motion. Students will also beexposed to Black-Sholes theory, which has applications infinancial engineering.
*Advanced knowledge of mathematics is required as thelevel is quite high.
Learn the basic concepts of various statistical methods
and how they are used in real life.

1

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