Jing Xiang

Staff Bioinformatics Scientist at GRAIL

Jing Xiang has a diverse work experience in the field of bioinformatics and machine learning. They started their career as a Research Assistant at University of Waterloo in 2006, where they worked for a year. In 2008, they worked as a Research Assistant at Queen's School of Computing. In 2010, Jing Xiang began working as a PhD Student at Carnegie Mellon University, specializing in applying machine learning to genomics. After completing their PhD, they took on the role of a Post Doctoral Researcher at Carnegie Mellon University, where they focused on using machine learning methods to understand transcriptional regulation in breast cancer. In 2012, they had a brief stint as a Research Intern at Microsoft. Since 2018, Jing Xiang has been working at GRAIL, Inc., where they initially served as a Senior Data Scientist and later transitioned into the role of a Staff Bioinformatics Scientist.

Jing Xiang completed a Bachelor's degree in Biomedical Computing at Queen's University from 2003 to 2008. During their undergraduate studies, they also participated in a Bachelor's degree Exchange Program at the University of Leeds from 2006 to 2007. After completing their Bachelor's degree, Jing Xiang pursued a Master of Applied Science in Biomedical Engineering at The University of British Columbia from 2008 to 2010. Lastly, Jing Xiang obtained a Doctor of Philosophy - PhD from Carnegie Mellon University, where they focused on an undisclosed field of study from 2010 to 2017.

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San Carlos, United States

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GRAIL

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GRAIL aims to develop a blood test to detect cancer early before symptoms appear offering higher survival rates compared to late-stage diagnosis.


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501-1,000

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