Republic of Korea
The Graduate School of Culture Technology (GSCT) at KAIST(*) invites applicants for tenure-track and non-tenure-track visiting faculty positions.
"Culture technology" is a multidisciplinary field drawing on virtually every aspect of our life, and evolves rapidly with the advancement of digital technology. In this respect, GSCT conducts research on cutting-edge technologies that enhance and transform our culture based on collaborations across a variety of disciplines including engineering, natural/social science, and liberal/visual arts.
We are looking for candidates for tenure-track positions in the broad areas of CT including but not limited to:
-Cognitive Science for human-culture research
-Complex systems, AI, NLP for cultural systems and information
An overview of current research and teaching programs at GSCT is available at http://ct.kaist.ac.kr.
Qualified candidates should hold doctoral degrees in any of the related areas, and possess outstanding academic or research credentials. Strong motivation to perform inter-disciplinary research across the diverse fields of engineering, arts, humanities is a must regardless of the candidate's original academic background.
The application and the publication list form are available here and should be sent to
Chair of the Search Committee
Graduate School of Culture Technology
291 Daehak-ro, Yuseong-gu Daejeon 34141, Republic of Korea
Although applications are accepted year-round, the above materials should be received on or before September 30th, 2017 for prompt initial consideration. The appointment can begin in the spring semester of 2018. Note that the full application can be sent after the candidate passes the pre-screening process. The passed candidate will be notified individually.
IMT School for Advanced Studies Lucca
Deadline for expressions of interest: September 15th 2017 at 11:59 PM, Italian time.
IMT School for Advanced Studies Lucca invites expressions of interest for an Associate Professor position in the area of complex systems and their analytical description by means of network theory. Candidates must have an excellent record of high-impact international publications with a distinctive multidisciplinary interest and a strong technical knowledge of statistical physics. Candidates must be active in the area of financial and economic networks. Interest and activities focused on neurosciences will be considered a plus.
Activities at the School include: research, tutorship and mentoring of PhD students, graduate teaching and grant applications. The successful candidate will be part of the Networks Research Unit and will collaborate in the shaping of the PhD program.
The deadline for submitting expressions of interest is September 15th 2017 at 11:59 pm, Italian time. The link to both the full description of the profiles and the online application form is included.
Network Science Institute at Northeastern University
The lab of Professor Albert-László Barabási, together with the Network Science Institute at Northeastern University and the Division of Network Medicine at Harvard University, is looking for postdoctoral associates in the area of network science, network medicine, and control theory. We are seeking motivated individuals with network science or control experience and interest in applying it towards both social and biological systems. The ideal candidate has a physics, bioinformatics, computer science or mathematics PhD, and previous work experience in networks and/or bioinformatics.
For a range of projects characterizing the lab see www.barabasilab.com. Our current work spans the applications of network towards understanding human diseases, to quantifying success in scientific careers, and understanding the fundamentals of network dynamics.
All interested candidates should submit a formal application consisting of (i) a current CV with publication lists, (ii) a brief statement of research experience and interests, and (iii) two letters of recommendation sent separately by the writers to:
James Stanfill at firstname.lastname@example.org or at Northeastern University, Center for Complex Network Research, 1100-177 Huntington Ave, Boston, MA 02115.