Job ID: 173283

Clinical Assistant Professor

University of North Texas

  • Nov. 24, 2021
 
  • Clinical Assistant Professor
  • UNT-Information Science-133310
  • University of North Texas
    Denton, TX
 
  • Open until filled
  • Fall 2022
  •  
 
  • Assistant Professor
  • Statistics & Actuarial Science
    Mathematics/Applied Mathematics
    Computer/Information Sciences
 
 
The Department of Information Science at the University of North Texas (UNT) invites applications for a non-tenure-track Clinical Assistant Professor position. Position will begin on Fall semester 2022. We are seeking excellent candidates with interests in a wide range of topics within the mathematical, statistical, machine learning, and computational foundations of data science and the applications of data science. We expect candidates can both successfully teach undergraduate and graduate Data Science courses as well as advise students in Data Science. The position carries a typical teaching load of three courses during the Fall and Spring semesters.

The successful candidate will teach introductory and upper-level courses in Data Science such as Data Curation, Data Modeling, Data Management, Data Mining, Big Data, Data Analysis, Machine Learning, Data Visualization, Computational Thinking for Problem Solving, Information and Data Security and Privacy, Information and Data Quality, Information Retrieval, and Data Science courses in the candidate’s area of expertise.

This is a nine month, full-time, non-tenure-track position. We seek candidates who will provide inspiration and leadership in research and teaching, who can leverage the strengths of the department’s dynamic faculty and programs, and who will build collaborative relationships in the University and profession.


The College of Information and Department of Information Science are committed to creating a learning community that reflects and enacts the values of diversity, equity and inclusion that inform academic excellence. We encourage applicants who may enhance our representational diversity but especially whose research, teaching, and community engagement will contribute to diverse, equitable, and inclusive learning and working environments for our students, staff, and faculty.

An offer of employment for this position will be made dependent upon available funding.

 
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