Welcome to Dr. Jennifer Beer's Self-Regulation Lab at the University of Texas at Austin!

  Postdoctoral Fellow Applicants: The Self-Regulation Lab at the University of Texas at Austin, directed by Jennifer Beer, is considering applications for a postdoctoral research fellow position starting in Fall 2017. The postdoctoral fellow will have the opportunity to develop their own projects. Current projects utilize computational modeling in combination with fMRI or ERP on topics of self, social cognition, motivated perception, and emotion.

Successful applicants will have a PhD in psychology, neuroscience, or a related field and a strong publication record which reflects expertise with fMRI. Applicants with additional expertise in computational modeling and advanced analytic methods (e.g., MVPA, DTI, network analyses) are especially encouraged to apply.

Applicants should send a CV and a statement of research interests which includes plans for research to be conducted while a postdoctoral researcher to Dr. Beer at beerutexas@gmail.com. 2-3 Referees should also send letters to Dr. Beer at beerutexas@gmail.com. Rolling review until positions are filled.


Self Regulation Lab

Front Row (L to R): Jessica Koski, Bridget Kajs, Jacie Richardson

Back Row (L to R): Ana Rigney, Jennifer Beer, Taru Flagan, Ellie Fogelman

Welcome to Jennifer Beer's lab!  Our research focuses on:
    Self
    Emotion, Motivation
    Social Cognition, Person Perception, Impression Formation

In our lab at the University of Texas at Austin, we're interested in how these processes contribute to appropriate social functioning. For example, how do our motivations to see ourselves and other people in particular ways impact our decisions in social interactions? At the moment, the main areas of our current research are the neural basis of motivational influences on social construal and perceiving other people in  light of new information.
 To address these questions, we use:
   
    Behavioral methods
    Behavioral observation (e.g., FACS coding)
    Computational modeling
    Self and peer-report

    Neuroscience methods
    Neuroimaging (fMRI, ERP)
    Patients with lesion