Assistant Professor



Job description

River Falls, WI

Appointment Type: Faculty

FTE: 100

Position Summary:

The Department of Computer Science and Information Systems at the College of Business and Economics, University of Wisconsin River Falls, AACSB International accredited, is seeking a tenure-track computer science faculty at the Assistant Professor level starting August 2019 (Preferred) or January 2020.

The qualified candidate should have a Ph.D. in Computer Science, Data Science or a related area (ABD with confirmed completion date prior to start of employment will be considered) and will be expected to teach introductory and advanced courses at the undergraduate and graduate level, develop curricula and assessment, maintain an active research agenda in computer science and/or data science, advise graduate and undergraduate majors, and provide service to both the university and the profession. The successful candidate will demonstrate excellent communication skills and ability to teach undergraduate and graduate courses in Computer Science and Data Science and is expected to teach in at least two of the four topics of Data Exploration and Analysis, Data Visualization, Data Storage and Retrieval, and/or Applied Machine Learning. Other teaching responsibilities will depend on expertise and departmental needs. Experience or interest in writing and submitting grant requests is a plus.

Through its strategic plan, Pathway to Distinction, UW-River Falls will vigorously pursue three goals: Distinctive Academic Excellence; Global Education and Engagement; Innovation and Partnerships. In support of our first goal, UW-River Falls strives to be a leader in collaborative and undergraduate research; we therefore seek faculty members who have an interest in or experience with faculty-student collaborative research, scholarship, and creative activity. The university is also interested in applicants who can support and extend our partnerships and initiatives in Asia and Latin America. The university’s strategic focus on international education encourages faculty to develop courses/pedagogy that facilitate the transition of international in-bound students and out-bound UWRF students and enhance our curricular and programmatic partnerships in these regions.

Knowledge, Skills and Abilities:

Qualifications (required):

  • Ph.D. in Data Science, Computer Science or a related area from an accredited institution. Applicants who have finished course work and are still working on their dissertation may be considered for a conditional appointment and must complete their Ph.D. by January 2020
  • Strong interest in and ability to teach an array of undergraduate and graduate classes in both Data Science and Computer Science.
  • Ability to teach in at least two of the four topics of Data Exploration and Analysis, Data Visualization, Data Storage and Retrieval, and Applied Machine Learning.
  • Demonstrate a commitment to scholarly activities that result in peer-reviewed publications
  • Strong interest in and ability to provide academic advising to undergraduate and graduate students
  • Interest in and ability to advise co-curricular activities such as student clubs/organizations, and internships
  • Strong interest in and ability to supervise undergraduate and graduate research.
  • Strong oral and written communication skills.
  • Demonstrated awareness of and sensitivity to diverse student populations and ability to contribute to the University’s commitment to enhancing student awareness and appreciation of diverse cultures, backgrounds, and identities.

Qualifications (preferred):

  • Experience or interest in writing and submitting grant requests
  • Teaching experience: Evidence of teaching effectiveness (most recent student evaluations and peer observations)

How to apply

Applicants are required to apply onlineUWRF will not consider paper, emailed or faxed applications.

Applicants are required to provide:

  • Letter of interest, detailing exactly how your qualifications and experience fit with the needs stated above (Upload as Cover Letter).
  • Curriculum Vitae
  • Unofficial graduate transcript (official copy will be required if hired). If uploading multiple documents, please upload all under one pdf.
  • Names, addresses and telephone numbers of at least three references who can specifically comment upon your teaching and research abilities and professional preparation (please note we are not asking for recommendation letters.)
  • Evidence of teaching effectiveness which should include a statement of teaching philosophy and may also include recent copies of student and/or peer evaluations (upload under Teaching Philosophy in one pdf document).

Inquiries should be addressed to:

Dr. Hossein Najafi, Professor and Search Committee Chair
Department of Computer Science and Information Systems
[email protected]

Deadline to Apply: Initial review of applications will begin upon receipt. For full consideration, applicants should submit all required materials by May 15,2019.

EEO/AA Statement:

UW-River Falls is an equal opportunity, affirmative action employer subject to all state and federal regulations pertaining to non-discrimination based upon sex, gender identity or expression, sexual orientation, race, color, national origin, religion, disability, marital status, age, arrest and/or conviction record, veteran or military status. All persons, especially women, minorities, veterans, and persons with disabilities are encouraged to apply.

Employment is subject to federal laws that require verification of your identity and legal right to work in the United States as required by the Immigration Reform and Control Act.

Confidentiality of Applicant Materials:

The University of Wisconsin System will not reveal the identities of applicants who request confidentiality in writing, except that the identity of the final candidates may be released. See Wis. Stat. sec. 19.36(7).

Annual Security and Fire Safety Report:

The Annual Security and Fire Safety Report, which includes statistics about reported crimes and information about campus security policies can be viewed at or call University Police at 715-425-3133 for a paper copy.