Hannah Douglas
About Hannah Douglas
Hannah Douglas is a Post Baccalaureate Research Fellow at The National Institutes of Health, specializing in neural computation and behavior. She holds a Bachelor's degree in Statistics and Neuroscience from Carnegie Mellon University and has experience in various research and data analysis roles.
Current Role at National Institutes of Health
Hannah Douglas serves as a Post-Baccalaureate Research Fellow at the National Institutes of Health (NIH) since 2020. In this role, she works in the Histed lab, focusing on neural computation and behavior. Her research utilizes two-photon optogenetic photostimulation techniques in mice, contributing to the understanding of neural mechanisms. This position allows her to apply her knowledge in neuroscience and engage in advanced research methodologies.
Education and Academic Background
Hannah Douglas completed her Bachelor's degree in Statistics and Neuroscience Track at Carnegie Mellon University from 2017 to 2020. Prior to this, she attended Cherry Creek High School from 2015 to 2017 and Chiang Mai International School from 2013 to 2015, where she achieved her High School Diplomas. Her academic journey laid a strong foundation for her research interests in neuroscience.
Previous Research and Teaching Experience
Before her current role, Hannah Douglas gained valuable experience in various research and teaching positions. She worked as a Research Assistant at the University of Pittsburgh from 2019 to 2020. Additionally, she served as a Probability Theory Teaching Assistant and a Statistical Computing Teaching Assistant at Carnegie Mellon University in 2018 and 2019, respectively. These roles enhanced her teaching skills and deepened her understanding of statistical concepts.
Internship Experience in Data Science
Hannah Douglas has completed several internships that contributed to her expertise in data analysis. She worked as a Data Scientist Intern at 84.51˚ for three months in 2019 and as a Data Analysis Intern at Club Prophet Systems for one month in 2018. These experiences provided her with practical skills in data analysis, particularly using R and Python, which she applies in her research.