Baldassano Ochsner Lab

Students will work on developing various tools for collecting and assessing affective responses to naturalistic stimuli, i.e. full length movies and pieces of music. The ultimate goal will be to build a web application that allows the user to continuously report their emotional responses along a number of affective dimensions in real time during the presentation of a stimulus. Specifically, some participants will be presented with a slider and use the LEFT and RIGHT arrows on the keyboard to rate how they are feeling along one continuous axis. Other participants will be presented with several different emotional terms and will be asked to select and deselect emotions. Students will also have the opportunity to integrate different models for analyzing the time series and test competing models for prediction accuracy.

Lab: Chris Baldassano/Kevin Ochsner 

Direct Supervisor: Matt Sachs

Position Dates: 11/19/2019 - 02/02/2020

Hours per Week: 20 (Flexible)

Paid Position: Potentially

Credit: Potentially

Positions Available: 1

Strong experience and aptitude in javascript/HTML. Experience in affective computing and/or time series analysis preferred but not required.