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The University of Texas at Austin is seeking a Postdoctoral Fellow for the Computational Affective and Social Cognition Lab. This full-time position involves leading research on AI and emotion, requiring a Ph.D. in Psychology or related fields. The lab studies the intersection of psychology and AI, focusing on how people and machines understand emotions.
The appointed fellow will manage data, mentor, and assist in grant writing while earning an annual salary of $70,000. Strong programming skills in R or Python are preferred.
Hiring Department: Department of Psychology
Position Open To: All Applicants
Weekly Scheduled Hours: 40
FLSA Status: Exempt from FLSA
Earliest Start Date: Immediately
Position Duration: Expected to Continue Until May 31, 2030
Location: UT MAIN CAMPUS
Job Details (General): The CASCog Lab, an interdisciplinary lab at the intersection of Psychology and Artificial Intelligence, is housed in the Department of Psychology, in the College of Liberal Arts at The University of Texas at Austin. The lab studies how people and machines understand emotions. Recent projects include investigating generative AI’s ability to provide empathy, examining how people perceive such artificial empathy, and exploring AI sycophancy and its implications for mental health. Lab website and Prof. Ong’s website. This is a fixed‑term position of one year.
Purpose: The Computational Affective and Social Cognition Lab (CASCogLab) is hiring a full‑time Postdoctoral Research Fellow for the academic year 2026‑27, directed by Professor Desmond Ong.
$70,000
Please ensure you meet all required qualifications and can perform the essential functions of the role with or without reasonable accommodation.
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.