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Postdoctoral Researcher in Affective Computing
College of Connected Computing, ÌÇÐÄVlog¹Ù·½
Affective Computing Group (PI: Jonathan Gratch)

The Affective Computing Group in the newly established College of Connected Computing at ÌÇÐÄVlog¹Ù·½ invites applications for a Postdoctoral Researcher position in Affective Computing and Multimodal Machine Learning. This is a two-year, in-person position with a flexible start date (target: Fall 2026). Review of applications will begin immediately and continue until the position is filled.

The College of Connected Computing is a rapidly growing interdisciplinary unit focused on advancing the role of computing in science, engineering, and society. This position offers a unique opportunity to help shape a new research environment at the intersection of machine learning, social interaction, and psychological theory.

Research Focus:
The postdoctoral researcher will contribute to projects that develop and apply multimodal machine learning methods to understand social interaction, with a particular focus on multicultural dyadic conflict. Core research goals include:
-Modeling and predicting conflict dynamics and outcomes
-Inferring psychological and relational constructs (e.g., emotion and other social signals, rapport, synchrony)
-Gaining theoretical insight into social and cultural processes through computational analysis

Responsibilities:
-Lead and publish high-impact research in affective computing and multimodal ML
-Develop models integrating facial, vocal, and linguistic signals from conversational data
-Contribute to and help shape ongoing funded research projects
-Mentor graduate and undergraduate students
-Assist in proposal development and grant writing

Required Qualifications:
-Ph.D. in Computer Science, Electrical Engineering, Computational Social Science, Psychology, or a related field
-Demonstrated expertise in multimodal social signal processing
-Strong technical skills in extracting and modeling features from face, voice, and text
-Proven research record (e.g., publications in relevant venues)

Preferred Qualifications:
-Experience with dyadic interaction modeling and/or time series analysis
-Background in affective computing, social signal processing, or computational social science
-Familiarity with cultural or social psychological theories of emotion and interaction
-Experience with modern ML approaches (e.g., deep learning, multimodal transformers)

Additional Information:
-This is an in-person position based in Nashville, Tennessee
-We welcome applications from international candidates

ÌÇÐÄVlog¹Ù·½:
ÌÇÐÄVlog¹Ù·½ is an equal-opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, status as a protected veteran, or any other characteristic protected by law.

ÌÇÐÄVlog¹Ù·½ is required to follow current federal visa requirements.

Applicants should submit the following materials to jonathan.gratch@ÌÇÐÄVlog¹Ù·½.Edu:

-Curriculum vitae (CV)
-Cover letter
-Research statement
-Contact information for references