The Doctoral Program in the Graduate School of Science and Engineering, Mathematical Informatics and Data Science Program, aims to foster researchers with original research capabilities and highly skilled engineers who will play a central role in regional industries. This is achieved through the active integration of science and engineering to address the advancement of science and technology in the interdisciplinary fields of mathematical informatics and data science.
Based on this educational objective, the degree of Doctor of Mathematical Informatics will be conferred upon those who complete the prescribed curriculum and achieve the following learning outcomes.

Fundamental Competencies

• Learning Outcomes: Acquire broad academic knowledge that forms the foundation for research and dissemination in science and engineering, and develop a comprehensive and global perspective necessary for solving various issues across disciplines.
  Develop English proficiency necessary for understanding original research papers and disseminating research findings.
• Indicators: Rich academic knowledge forming the basis of science and engineering research and dissemination; reading comprehension, logical thinking, and language skills for understanding original papers.
  Expressive and language skills for disseminating research results.

Specialized Knowledge

• Learning Outcomes: Understand world-class research outcomes and methodologies in mathematical informatics and data science, and acquire the abilities required for highly specialized professions based on science and engineering research.
• Indicators: Ability to understand advanced outcomes and methodologies in mathematical informatics and data science.

Ethics

• Learning Outcomes: Develop a normative awareness of research ethics.
• Indicators: Possess a normative awareness of research ethics and conduct research activities in accordance with ethical standards.

Creativity

• Learning Outcomes: Acquire the ability to plan and promote original research based on prior studies, and to compile and present the results in academic papers.
• Indicators: Research planning ability, promotion ability, and dissemination ability.

The Doctoral Program in the Graduate School of Science and Engineering, Mathematical Informatics and Data Science Program, organizes a systematic curriculum to develop the four competencies outlined in the diploma policy.

Over three years of study, the curriculum is implemented to enable students to learn proactively and actively. In addition to required courses such as seminars and special research, students can select lecture courses from their own program and other programs. Evaluation is based on objective grading criteria regarding the achievement level of learning outcomes for each competency.

Fundamental Competencies

• Content: Acquire knowledge and a broad perspective necessary to identify and solve new problems in various fields of science and engineering or in interdisciplinary areas with medicine and pharmacy.
• Methods: Study courses offered by own or other programs.
• Evaluation: Evaluated by instructors through exams, reports, and presentations.

Specialized Knowledge

• Content: Study highly specialized courses in mathematical informatics and data science, and deepen expertise through reading academic papers and participating in conferences. Plan and promote doctoral research through discussions with advisors, and compile and present results in academic papers.
• Methods: Study courses related to own research theme, read academic papers, and participate in conferences.
• Evaluation: Evaluated by faculty members through final exams, presentations, and submitted academic papers.

Ethics

• Content: Develop normative awareness of research ethics, including compliance with laws and regulations during research.
• Methods: Study through participation in various workshops or e-learning materials.
• Evaluation: Evaluated through reports or completion of learning materials depending on the content.

Creativity

• Content: Acquire the ability to plan, promote, and present original research based on prior studies.
• Methods: Learn through conducting research, writing papers, and presenting at academic conferences and workshops.
• Evaluation: Evaluated by faculty members through final exams, presentations, and submitted academic papers.

The Doctoral Program in the Department of Science and Engineering, Graduate School of Science and Engineering, Mathematical Informatics and Data Science Program seeks motivated students who aspire to become advanced professionals and researchers in mathematical informatics. These individuals will lead technological innovation through mathematics, informatics, and data science, and contribute to enhancing the well-being of local communities.

To provide multiple opportunities for applicants and to evaluate a diverse range of students, the following types of entrance examinations are offered:

General Entrance Examination

Evaluation is based on oral examination, interview, and document review, focusing on English proficiency, subjects related to the desired field of study, the master’s thesis, and the research plan after admission.

Special Entrance Examination for Working Professionals

Evaluation is based on oral examination, interview, and application documents, focusing on subjects related to the desired field of study, academic papers, achievement reports, patents, and the research plan after admission.

Early Completion Entrance Examination for Working Professionals

Evaluation is based on oral examination, interview, and application documents, focusing on subjects related to the desired field of study, academic papers, achievement reports, patents, and the doctoral dissertation proposal.

Special Entrance Examination for International Students

Evaluation is based on oral examination, interview, and application documents, focusing on language proficiency required for doctoral-level education, subjects related to the desired field of study, the master’s thesis, and the research plan after admission.

Fundamental Competencies

Students should have a strong desire to acquire broad knowledge in various academic fields centered on science and engineering, and possess foundational academic abilities equivalent to a master’s degree, including comprehension, logical thinking, and expressive skills.

Specialized Knowledge

Students should have a deep interest in mathematical informatics and data science, and be motivated to acquire specialized knowledge and practical skills through research, aiming to contribute to society.

Ethics

Students should have a sense of responsibility and ethics as members of society, and be aware of contributing to the sound development of science and technology through independent research.

Creativity

Students should possess strong research motivation and flexible thinking skills to tackle unknown and cutting-edge problems, aiming to contribute to both local and global communities.