Mary Wood

Mary Wood has extensive experience in the field of genomics and bioinformatics. Mary worked at Phase Genomics as a Data Scientist, where they developed shallow and deep learning models to predict structural variation from sequencing data and trained machine learning models to detect structural variants and predict chromosome ploidy. Prior to that, Mary was a Bioinformatics Research Analyst at Phase Genomics, where they performed genomic analyses and provided guidance to customers on experimental design and result interpretation.

Before their time at Phase Genomics, Mary worked as a Research Associate at the PORTLAND VA RESEARCH FOUNDATION INC, where they developed and benchmarked python software for neoepitope prediction. Mary also worked as a Computational Biology Intern at Oregon Health and Science University. In addition, Mary has teaching experience as a Graduate Teaching Fellow at the University of Oregon and worked as an Undergraduate Research Assistant at the same institution. Mary also conducted research as a Graduate Researcher at the Bradshaw-Holzapfel Laboratory and as part of Dr. Alice Barkan's Advanced Molecular Biology Research Lab at the University of Oregon.

Overall, Mary brings a strong background in genomics, bioinformatics, and data analysis to their work experiences.

Mary Wood obtained their Master's Degree in Biology - Bioinformatics from the University of Oregon Graduate School, from 2015 to 2017. Prior to that, they earned their Bachelor's Degree in Biology, General from the University of Oregon, from 2010 to 2014. Mary completed their high school education at West Linn High School, where they received their high school diploma from 2006 to 2010.

In addition to their formal education, Mary has also obtained various certifications. Mary completed the Generative Adversarial Networks (GANs) Specialization at DeepLearning.AI in December 2022. In March 2021, they completed the Deep Learning Specialization, also at DeepLearning.AI. Furthermore, Mary obtained the Try Docker certification from Code School in April 2017.