2016 International Internship on Computational Life Sciences for Doctoral Students

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Academic unit or major
Education Academy of Computational Life Sciences
Instructor(s)
Kajiwara Susumu 
Course component(s)
Day/Period(Room No.)
Internship ()  
Group
-
Course number
ACL.C601
Credits
4
Academic year
2016
Offered quarter
3-4Q
Syllabus updated
2017/1/11
Lecture notes updated
-
Language used
English
Access Index

Course description and aims

This course for doctoral students is aimed at enhancing their qualifications as future international leaders through three-month overseas internships, improving their intercultural communication and problem-solving skills, and facilitating their acquiring advanced debate and collaboration skills on academic researches.
Students' qualifications will be assessed with the written report and presentation after the end of the internship from the viewpoint of the qualities for doctor.

Student learning outcomes

By completing this course, students acquire the following:
1) Ability to understand the study in “Computational Life Science” field based on the research at the host agency.
2) Balanced research skills to combine the knowledge acquired at both the students' laboratory and the host agency.
3) Practical and problem-solving skills for advanced research in the field of “Computational Life Science”

Keywords

Intercultural Skills, Internship

Competencies that will be developed

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

Class flow

After discussion with ACLS advisors, students receive training at their host agencies. After completing the training, students submit activity reports about their training.

Course schedule/Required learning

  Course schedule Required learning
Class 1 To be announced by each host. To be announced by each host.

Textbook(s)

Specified as necessary.

Reference books, course materials, etc.

Specified as necessary.

Assessment criteria and methods

Students are evaluated based on their activity at the host and their report.

Related courses

  • LST.C505 : Short-term Internship on Computational Life Sciences

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

This course is offered by Education Academy of Computational Life Sciences (ACLS).
This course is unacceptable as credits for students, who are not enrolled in ACLS.

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