Öğretim Üyesi İlanı

The Department of Industrial Engineering at Boğaziçi University invites applications for a full-time tenure-track faculty position starting in Spring 2020. Candidates are expected to have a PhD in industrial engineering, operations research, statistics, management sciences, or a related field. The department encourages candidates with background and interest in smart manufacturing and would consider applicants with strong academic records in methodological or applied topics.

Applications should include a statement of research and teaching interests, curriculum vitae, and the names and contact information of at least three references. Please send all applications and nominations by November 30, 2019 via e-mail to Professor Necati Aras, Chair, Department of Industrial Engineering, Boğaziçi University, 34342 Bebek – Istanbul, Turkey, E-mail:

The candidates who are shortlisted are expected to make a formal oral presentation of their research.

Officially established as a public university in 1971, Boğaziçi University originated as the Robert College, founded in 1863 in Istanbul - the first American college established outside the US. The language of instruction is English throughout the University. Department of Industrial Engineering at Boğaziçi has the highest staff-to-student ratio in the nation and attracts the best students both at the undergraduate and graduate levels. Boğaziçi IE program is accredited by ABET since 1997 along with all Engineering programs of the University.

Information about the university and the Department can be found at, respectively, http://www.boun.edu.tr/ and http://www.ie.boun.edu.tr/.

JOB DESCRIPTION

The Department of Industrial Engineering at Boğaziçi University (BU) in İstanbul, Turkey looks for a full-time assistant professor in the area of smart manufacturing. The position will support the Department in manufacturing and production domains, with a focus on digitalization and Industry 4.0; and requires a strong background in quantitative methods such as operations research, machine learning, data analytics, manufacturing paradigms, and the use of information technology.

The assistant professor will become a member of the Flexible Automation and Intelligent Manufacturing Systems (BUFAIM) Laboratory. BUFAIM, founded in 2001, aims to realize a flexible and smart manufacturing environment where research on modern manufacturing planning and control techniques, flexible automation concepts and their integration issues can be conducted.  The Model Factory in BUFAIM is run by means of in-house developed software, and provides a reconfigurable infrastructure for implementing the on-going research and presenting it to academia and industry. BUFAIM’s research objectives are in line with the recently promoted “Industry 4.0” concept that refers to the use of digital technologies to integrate in real-time all components over the value chains. Over the years, BUFAIM has accumulated a substantial level of knowledge regarding the manufacturing flexibility concept and significant experience in the fields of modelling, simulation and real-time management of manufacturing systems through many graduate thesis work, as well as national and international projects.

The responsibilities expected from the position cover the following:

  • The assistant professor will be willing to cooperate with colleagues at the department and with other departments of BU; to actively participate in future Industry 4.0 initiatives of the Department; and to build collaborations with industry.
  • The assistant professor will conduct research in quantitative methods to strengthen the capabilities of the department in the smart manufacturing domain (e.g. simulation and digital twin; distributed control; augmented reality; factory logistics and its integration with the supply chain; product lifecycle management, predictive maintenance.)  
  • The assistant professor will participate in teaching Bachelor-, Master- and PhD-level courses, and act as supervisor for MS and PhD students. The candidate is expected to teach domain specific courses similar to IE 414 and IE 486; some of the required departmental courses such as IE 220, IE 312 or IE 413, and design new elective courses.  All courses are taught in English, and  candidates should have fluency in both spoken and written English