2017 Topics 4 in Computational Life Sciences for Doctoral Students

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Academic unit or major
Education Academy of Computational Life Sciences
Instructor(s)
Tokunaga Makio 
Course component(s)
Lecture
Mode of instruction
 
Day/Period(Room No.)
Intensive ()  
Group
-
Course number
ACL.A634
Credits
1
Academic year
2017
Offered quarter
3-4Q
Syllabus updated
2017/10/4
Lecture notes updated
-
Language used
Japanese
Access Index

Course description and aims

This course for doctoral students aims to develop expertise by learning about the latest findings and cutting edge research.
Distinguished researchers in computational life sciences or outstandingly active specialists beyond academia in various fields such as industry or government service give introductory lectures of the latest research frontiers or technology trends.

Student learning outcomes

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

Keywords

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 Frontiers or topics on computational life sciences (1): Introduction of the field and topics is given by an invited researcher. Understand the basics and backgrounds on the frontiers or topics in computational life sciences.
Class 2 Frontiers or topics on computational life sciences (2): Detailed lecture is given to deepen understanding and expertness. Understand and explain the essential features and matters on the frontiers or topics in computational life sciences.
Class 3 Frontiers or topics on computational life sciences (3): Subjects to contribute to enhancement of the qualifications and abilities of the Γ(gamma)-type specialist are given, and discussions take place among students and the researcher. Enhance the qualifications and abilities of the Γ(gamma)-type specialist based on the frontiers or topics in computational life sciences.

Textbook(s)

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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