Graduate Research Assistant

Develop and refine reproducible data-processing pipelines for high-frequency ambulatory sensor data collected from a wearable device, with primary emphasis on the Empatica EmbracePlus.Organize, clean, and perform quality assessment on raw and processed Empatica data, including electrodermal activity, heart rate, PPG-derived measures such as HRV, accelerometry-derived measures such as activity and sleep/wake patterns, skin temperature, and related time-stamped sensor streams.Develop procedures for data quality assessment, signal review, feature extraction, and preparation of analysis-ready datasets from two-week ambulatory sensor collection periods.Support the integration of ambulatory sensor data with survey data, two-week daily diary data, and related participant metadata.Develop and maintain code for data pre-processing, post-processing, and integration. MATLAB is preferred, though experience with Python or R will also be considered.Use GitHub for version control and reproducible research workflows. Create clear documentation, workflow notes, and annotated code to support future use of the data-processing pipelines.Collaborate with research team members to troubleshoot data-processing issues, improve workflow design, and follow secure, ethical, and IRB-compliant data-handling protocols.As project needs develop, assist with related processing workflows for data from a lab-based electrophysiological experiment.