Profile
Behavioral neuroscience research assistant with 4 years of hands-on experience in rodent models, electrophysiology, and cognitive behavioral paradigms at R1 universities. Proficient in MATLAB, Python, and SPSS for data pipeline automation and statistical analysis of large neuroimaging datasets. Co-authored 2 peer-reviewed publications and reduced data-processing time by 38% through custom preprocessing scripts.
Work Experience
- Designed and executed 14 fear-conditioning behavioral protocols across 120+ rodent subjects, achieving 94% data-quality yield and reducing trial attrition by 22%.
- Automated EEG artifact-rejection pipeline in Python, cutting preprocessing time from 6 hours to under 2 hours per dataset and eliminating manual entry errors across 3,400 recordings.
- Mentored 4 undergraduate volunteers on stereotaxic surgery prep and histology procedures, reducing supervisor intervention requests by 60% within one semester.
- Recruited and screened 210 adult participants for fMRI studies on working memory, maintaining IRB-compliant consent records with zero protocol deviations over 20 months.
- Processed and quality-checked 1.8 TB of BOLD-signal neuroimaging data using FSL and SPM12, contributing to analyses published in NeuroImage (2022).
- Built an automated scheduling dashboard in Google Apps Script that reduced participant no-show rates by 31% and saved the lab coordinator 5 hours per week.
- Coded 640 hours of observational video data for an NIH-funded childhood stress study using Datavyu, reaching 96% inter-rater reliability with the senior coder.
- Assisted with literature synthesis for 3 grant submissions totaling $480,000 in requested funding, 2 of which were awarded.
- Prepared and stained 300+ histological brain sections using cresyl violet protocol, supporting publication-quality imaging for 1 journal article.