Ernest Lam
About Ernest Lam
Ernest Lam serves as the Director of Bioinformatics at Epic Sciences, where he focuses on enhancing bioinformatics capabilities and leading diagnostic test development. He has extensive experience in bioinformatics and holds a PhD in Pharmaceutical Sciences and Pharmacogenomics from UCSF.
Current Role at Epic Sciences
Ernest Lam serves as the Director of Bioinformatics at Epic Sciences, a position he has held since 2021. In this role, he is responsible for building the company's bioinformatics capabilities, which includes overseeing personnel and the technology stack. His work focuses on enhancing the analytical frameworks that support the company's diagnostic initiatives.
Previous Experience at Bionano Genomics, Inc.
Before joining Epic Sciences, Ernest Lam worked at Bionano Genomics, Inc. as a Senior Manager in Bioinformatics from 2012 to 2021. During his nine years in this role, he contributed to the development and implementation of bioinformatics strategies that supported genomic research and applications.
Academic Background and Education
Ernest Lam earned a Bachelor of Science in Pharmacological Chemistry with honors from the University of California, San Diego (UCSD) from 2004 to 2007. He then pursued a Doctor of Philosophy in Pharmaceutical Sciences and Pharmacogenomics at the University of California, San Francisco (UCSF), completing his studies from 2007 to 2012.
Teaching and Research Experience at UCSF
During his time at UCSF, Ernest Lam held multiple roles, including Doctoral Student and Teaching Assistant from 2007 to 2012. He also volunteered as a scientist from 2007 to 2011. His involvement in these positions allowed him to support various biomarker discovery projects and contribute to academic publications.
Contributions to Diagnostic Testing
Ernest Lam leads the launch of DefineMBC, a multi-modal comprehensive diagnostic test for metastatic breast cancer. His expertise includes applying data science and machine learning methods to complex datasets, as well as developing and validating algorithms for translational research and clinical applications.