Faculty Position Announcement
Department of Industrial & Systems Engineering, KAIST
Jan 4, 2021
The Department of Industrial & Systems Engineering at KAIST invites applications for tenure-track faculty positions at the levels of Associate/Assistant Professor. KAIST is a globally renowned science and technology institution, particularly well known for its excellence in engineering and technology. The institute is dedicated to promoting a vibrant academic culture and offers an internationally-minded environment through ways such as teaching all courses in English.
Applicants should have a background in disciplines in industrial engineering and/or related fields of engineering. We seek candidates who are genuinely interested in solving complex system design and operations problems in manufacturing and service industries. In particular, we invite applicants in the areas related to Analytics with a focus on Dynamic Learning and Business Analytics. That being said, we expect applicants to have the ability to apply machine learning or data scientific methods to solve classical and new problems in industrial engineering.
Industrial or academic experience will be considered preferably, and students who are expected to complete their PhDs until the end of July 2021 will also be considered. Application documents along with an up-to-date CV should be sent to:
Professor Kyoung-Kuk Kim
Application materials should be submitted no later than Jan 20th to receive full consideration.
For general information about the Department of Industrial & Systems Engineering at KAIST, please visit http://ie.kaist.ac.kr. You can also find out more about KAIST at http://kaist.ac.kr. If you have further inquiries regarding this faculty position announcement such as targeting areas, you may contact Prof. Kyoung-Kuk Kim at firstname.lastname@example.org.
Invitations for other areas such as (but not limited to) optimization theory, artificial intelligence, or human factors will be separately posted in the near future.
The Institute for Operations Research and the Management Sciences
phone 1 443-757-3500
phone 2 800-4INFORMS (800-446-3676)