Computer Science & Engineering, University of Connecticut

Position ID:UConn-CSE-2018165 [#10093, 2018165]
Position Title: Assistant Professor (Tenure track)
Position Type:Tenured/Tenure-track faculty
Position Location:Storrs, Connecticut 06269, United States [map]
Subject Areas: Computer Science / Data Mining, Machine Learning
Appl Deadline: finished (posted 2017/10/09, finished 2018/11/02)
Position Description:    

*** this position has been closed, and no new applications will be accepted. ***

* this map is a best-effort approximation. Open in Google Maps directly.

The Computer Science & Engineering (CSE) Department at the University of Connecticut invites applications for a tenure track faculty position at the assistant professor level. The position is expected to start on August 23, 2018. The department is looking for a Computer Scientist specializing in Machine Learning or Data Mining with applications in manufacturing. 

The University of Connecticut (UConn) is entering a transformational period of growth supported by the $1.7B Next Generation Connecticut ( ), the $1B Bioscience Connecticut ( ) investments, and a bold new Academic Plan: Path to Excellence ( ).  As part of these initiatives, UConn has hired more than 450 new faculty members at all ranks during the past five years.  We are pleased to continue these investments by inviting applications for a new position in Machine Learning or Data Mining. The Department of Computer Science & Engineering harbors a rich environment of instruction and research, offering three rigorous degrees (B.S., M.S., and Ph.D.) in the computing sciences and a world-class research enterprise. Additional information about the department can be found at .


Successful candidates will be expected to develop and sustain an internationally-recognized and externally-funded research program in Computer Science with specialization in the fields of Machine Learning or Data Mining, with particular interest in research with applications to manufacturing.  Successful candidates must share a deep commitment to effective instruction in Computer Science at the undergraduate and graduate levels as well as development of innovative courses and mentoring of students in research, outreach, and professional development.  Successful candidates are also expected to broaden participation among members of under-represented groups; demonstrate through their teaching, research, and/or public engagement the richness of diversity in the learning experience; and provide leadership in developing pedagogical techniques designed to meet the needs of diverse learning styles and intellectual interests.


Candidates must have an earned Ph.D. in Computer Science or a related field by the time of appointment; an established record of research in computing sciences with a specialty in Machine Learning or Data Mining with particular interest in applications in manufacturing; demonstrated potential for excellence in teaching; and a commitment to promoting diversity through their academic and research programs. Candidates must also demonstrate a commitment to graduate education.


Preferred candidates will possess an outstanding record of scholarship and research contributions in Computer Science, and have accomplishments showing relevance of their research to manufacturing applications; a record of excellence in teaching; the ability to effectively communicate with students in both large and small audiences, and a record of public engagement.


This is a full-time, 9-month tenure track position.  Employment is conditional upon the timely completion of an approved I-9 (Employment Eligibility Verification Form). Candidates are expected to begin work on August 23, 2018. Salary will be commensurate with qualifications.


Select “Apply Now” to be redirected to Academic Jobs Online to complete your application. Please submit the following: a cover letter, curriculum vitae, research and scholarship statement; teaching statement (including teaching philosophy, teaching experience, commitment to effective learning, concepts for new course development, etc.); commitment to diversity statement (including broadening participation, integrating multicultural experiences in instruction and research and pedagogical techniques to meet the needs of diverse learning styles, etc.); and sample articles or books.  Additionally, please follow the instructions in Academic Jobs Online to direct three reference writers to submit three professional letters of reference on your behalf.  Screening of applicants will begin immediately and continue until the position is filled. Employment of the successful candidates will be contingent upon the successful completion of a pre-employment criminal background check. (Search # 2017165)

All employees are subject to adherence to the State Code of Ethics which may be found at .

The University of Connecticut is committed to building and supporting a multicultural and diverse community of students, faculty and staff. The diversity of students, faculty and staff continues to increase, as does the number of honors students, valedictorians and salutatorians who consistently make UConn their top choice. More than 100 research centers and institutes serve the University’s teaching, research, diversity, and outreach missions, leading to UConn’s ranking as one of the nation’s top research universities. UConn’s faculty and staff are the critical link to fostering and expanding our vibrant, multicultural and diverse University community. As an Affirmative Action/Equal Employment Opportunity employer, UConn encourages applications from women, veterans, people with disabilities and members of traditionally underrepresented populations.

Application Materials Required:
Submit the following items online at this website to complete your application:
And anything else requested in the position description.

Further Info:
Computer Science & Engineering Department
371 Fairfield Way, Unit 4155
University of Connecticut
Storrs, CT 06269-4155
Phone: (860) 486-3719
Fax: (860) 486-4817

© 2018 AcademicJobsOnline.Org. All Rights Reserved.