Caitlin E Carey
About Caitlin E Carey
Caitlin E Carey is a Postdoctoral Associate at the Broad Institute of MIT and Harvard, where she has worked since 2017. She holds a PhD in Psychology from Washington University in St. Louis and has extensive experience in genetic analysis and statistical modeling.
Work at Broad Institute
Caitlin E Carey has been a Postdoctoral Associate at the Broad Institute of MIT and Harvard since 2017. In this role, she has contributed to significant research projects, including leading a large-scale phenotypic dimensionality reduction of the UK Biobank. Her work involves advanced statistical modeling and the analysis of genetic and longitudinal outcomes. She has also supervised and trained Associate Computational Biologists in genetic quality control for various studies.
Education and Expertise
Caitlin E Carey earned her Bachelor of Arts in Psychology from Harvard University, studying from 2009 to 2012. She then pursued a Doctor of Philosophy in Psychology at Washington University in St. Louis, completing her studies from 2012 to 2017. Her educational background has provided her with a strong foundation in psychological research methodologies and statistical analysis, which she applies in her current research.
Previous Work Experience
Before her current position, Caitlin E Carey held several roles in academia and research. She worked as a Course Instructor at Maryville University of Saint Louis for three months in 2016. From 2012 to 2017, she served as a Graduate Research Assistant at Washington University in St. Louis. Earlier, she was an Undergraduate Research Assistant at Harvard University from 2010 to 2012 and a Summer Research Assistant at Massachusetts General Hospital in 2010.
Research Contributions
Caitlin E Carey has made significant contributions to genetic research, including conducting hundreds of genome-wide association studies (GWAS) using various software packages. She co-led the largest GWAS meta-analysis of autism through the Psychiatric Genomics Consortium and was part of a team that publicly released GWAS of over 4000 traits in the UK Biobank. Her work also includes advanced analyses of GWAS summary statistics and the investigation of genetic architecture related to survey nonresponse.
Technical Skills and Methodologies
Caitlin E Carey possesses extensive experience in using programming languages such as Python and R on high-performance computing (HPC) and cloud-based platforms. She employs advanced statistical modeling techniques, including structural equation modeling and survival modeling, in her research. Her expertise extends to working with multimodal data at the terabyte scale, integrating genetic, neuroimaging, and phenotypic data for comprehensive analyses.