Postgraduate Associate for Academic Integrity

Job Posting Title: Postgraduate Associate for Academic Integrity Hiring Department: College of Liberal Arts Location: UT Main Campus Weekly Scheduled Hours: 40 FLSA Status: Exempt from FLSA Earliest Start Date: Immediately Position Duration: Expected to Continue Until Jun 01, 2028 Purpose Manage, maintain, and further develop online course academic integrity methods and approaches, with a focus on anomaly detection and cheating detection, in support of Liberal Arts Instructional Technology Services (LAITS)-supported online courses and programs for campus. Responsibilities Manage current Academic Honesty support efforts for LAITS online courses. Consult with instructors about available academic honesty tools such as TOWER, Honorlock, TurnItIn, etc. Develop support plans with instructors. Coordinate with graduate student employees as needed to execute support plans or provide support directly. Product manage the TOWER Academic Honesty tool. Advise LAITS instructors on isolated incidents of academic misconduct. Research, develop, and execute new or underutilized rigorous methods, processes, and capabilities for detecting cheating and promoting academic integrity. Design and implement efficient quantitative analyses to improve current methods and/or their interpretability. Research, develop, test new and updated cheating/anomaly detection methods using rigorous computational and/or quantitative methods. Take independence to plan, test, and implement other relevant methods and development avenues of interest in consultation with supervisor. Perform additional related functions as assigned. Required Qualifications Master's Degree, or imminent or recent completion of PhD, in a related field. Four years of experience in data science, statistics, behavioral social science, or a similar research-focused field. Fluency with common statistical programming and software such as R or Python, probability distributions (especially discrete probability distributions such as the binomial distribution), and data analysis including, but not limited to, data mining, descriptive statistics, multivariate modelling, and data visualization. Proficiency with permutation testing and/or bootstrapping techniques, research design, and data collection. Ability to learn new approaches and techniques as the need arises. Teaching or TA experience at the college level. Demonstrated understanding and experience with learning technology practices and software including, but not limited to, online courses and learning management systems. Interest in quantitative methods and working on processes, systems, and tools that promote academic integrity and student well‑being. Relevant education and experience may be substituted as appropriate. Preferred Qualifications Master's Degree, or imminent or recent completion of PhD, especially from the University of Texas at Austin. Skilled with quantitative methods in educational psychology, psychometrics, statistical modeling, etc. Experience with online teaching and learning, especially at the college undergraduate level. Experience with learning management platforms, especially Canvas. Demonstrated experience in seeking opportunities to improve processes and optimize work functions. Professional experience in a university setting. Salary Range $60,000 + depending on qualifications. Working Conditions May work around standard office conditions. Repetitive use of a keyboard at a workstation. Will work on multiple projects concurrently, under pressure of rigid deadlines and time limitations. Overtime, evening, weekend, and holiday work may be required to meet project deadlines. Work location is on the main UT campus. Equal Opportunity Employer The University of Texas at Austin, as an equal opportunity/affirmative action employer, complies with all applicable federal and state laws regarding nondiscrimination and affirmative action. The University is committed to a policy of equal opportunity for all persons and does not discriminate on the basis of race, color, national origin, age, marital status, sex, sexual orientation, gender identity, gender expression, disability, religion, or veteran status in employment, educational programs and activities, and admissions. Employment Eligibility Verification Standard employment eligibility verification applies. All applicants must present acceptable and original documents to prove identity and authorization to work in the United States by the third day of employment. Background Checks A criminal history background check will be required for finalists under consideration for this position. E‑Verify E‑Verify is used to check work authorization of new hires effective May 2015. University ID number for E‑Verify is 854197. Pay Transparency The University will not discriminate based on inquiry or discussion of pay. Employees who have access to compensation information must maintain confidentiality except in formal or investigative contexts. #J-18808-Ljbffr Phase2 Technology