Elizabeth Chin

Elizabeth Chin, PhD has a diverse work experience in various scientific and research roles. Elizabeth is currently working as a Data Scientist at GenMark Diagnostics since March 2022. Previously, they held the position of Computational Biologist Research Associate at the US Department of Agriculture (USDA) Agricultural Research Service (ARS) from July 2019 to March 2022. Prior to that, they worked as a Postdoctoral Researcher at UC Davis Genome Center from June 2018 to June 2019.

Elizabeth also gained valuable experience as an Intern at the California Institute of Food and Agricultural Research (CIFAR) from October 2012 to June 2018. Elizabeth pursued their Ph.D. at UC Davis Food Science and Technology from July 2012 to August 2017, during which they were a Ph.D. Candidate.

Elizabeth's earlier experiences include internships at PepsiCo and The Hershey Company, where they worked in Research and Development in the field of microbiology. Elizabeth also served as an Undergraduate Research Assistant at Virginia Tech Food Science and Technology from 2008 to 2011.

Elizabeth Chin, PhD completed their education in the field of Food Science and Technology. Elizabeth earned their Bachelor's degree from Virginia Tech in 2012, focusing on Food Science and Technology, with a minor in Biological Sciences w/ Chemistry. Elizabeth went on to pursue a Doctor of Philosophy (Ph.D.) at the University of California, Davis, specializing in Food Science and Technology. Elizabeth started their PhD program in 2012 and the end date is not provided.

In addition to their formal education, Elizabeth Chin has obtained several certifications from Coursera. Elizabeth completed the Deep Learning Specialization and Sequence Models in April 2021. In January 2021, they completed the Convolutional Neural Networks certification. Elizabeth also obtained the certificate for Structuring Machine Learning Projects in December 2020. There were two other certifications mentioned, "Improving Deep Neural Networks: Hyperparameter tuning, Regularization, and Optimization" and "Neural Networks and Deep Learning," but the completion details were not provided.