2016 Topics 4 in Computational Life Sciences for Doctoral Students

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Academic unit or major
Education Academy of Computational Life Sciences
Yamaguchi Yuki  Harada Takashi 
Course component(s)
Day/Period(Room No.)
Intensive ()  
Course number
Academic year
Offered quarter
Syllabus updated
Lecture notes updated
Language used
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Course description and aims

This course for doctoral students aims to develop expertise by learning about the latest findings and cutting edge research.

Student learning outcomes

By the end of this course, doctoral students will gain knowledge about the relationship between specialists and society.


relationship between science and engineering-related personnel and society, career-path, specialist

Competencies that will be developed

Specialist skills Intercultural skills Communication skills Critical thinking skills Practical and/or problem-solving skills

Class flow

A series of lectures are offered as an intensive course.
Each class session consists of two 90-minute lectures with an intermission between them.

Course schedule/Required learning

  Course schedule Required learning
Class 1 November 2nd (1)14:05~14:50 takashi Harada(ACLS, Tokyo Tech.) (2)15:05~16:35 Hideyoshi Okayasu(Boston Consulting Group) (1)Why the society needs the science and engineering-related personnel (2)Consultant
Class 2 November 16th (1)13:20~14:50 Shouji Kodama(Nikkei Inc.) (2)15:05~16:35 Kumi Shimane(Toshima Accounting Firm) (1)Journalist (2)Certified Public Accountant
Class 3 November 30th (1)13:20~14:50 Takaaki Kono(A. Koike & Co. Patent Firm) (2)15:05~16:35 Mizuho Takeda(MVP Inc.) (1)patent attorney (2) License Associate
Class 4 December 7th (1)13:20~14:50 Tomoki Nikaido(Japan Science and Technology Agency :JST) (2)15:05~16:35 Manabu Shikauchi(Recruit Career Co., Ltd.) (1) Funding Agency's staff (2)Viewpoint of the career path construction


There is no assigned textbook.

Reference books, course materials, etc.

In each class, the lecturer hands out materials.

Assessment criteria and methods

Reports in each class (100%).

Related courses

  • Nothing

Prerequisites (i.e., required knowledge, skills, courses, etc.)

There are no prerequisites for taking the course.

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