Sidharth Jain
About Sidharth Jain
Sidharth Jain is an Associate Computational Biologist at the Broad Institute, where he has worked since 2017. He has a background in biology and has held various research positions at institutions such as Boston Children's Hospital, Icahn School of Medicine at Mount Sinai, and Harvard Medical School.
Work at Broad Institute
Sidharth Jain has been employed at the Broad Institute since 2017 as an Associate Computational Biologist. In this role, he focuses on integrating data analytics with biological research to advance medical science. His work involves interdisciplinary research that combines computational methods with biological data, addressing complex medical challenges. Jain participates in collaborative efforts at the Broad Institute aimed at developing innovative solutions in the field of medicine through data-driven approaches.
Previous Research Experience
Before joining the Broad Institute, Sidharth Jain held various research positions. He worked as a Research Assistant at Boston Children's Hospital for two months in 2012. He then served at the Icahn School of Medicine at Mount Sinai from 2014 to 2015 for 11 months. Additionally, he was a Summer Intern at Harvard Medical School in 2015 for three months. Jain also worked as a Student Research Assistant at New York University from 2015 to 2016 and as a Research Assistant at the same institution from 2014 to 2015.
Education and Academic Background
Sidharth Jain studied at New York University, where he earned a Bachelor of Arts degree in Biology from 2013 to 2017. His academic background provided him with a solid foundation in biological sciences, which he has applied throughout his career in computational biology. Prior to his university education, he attended Northern Valley Regional Demarest High School.
Data Analysis Experience
In addition to his research roles, Sidharth Jain worked as a Data Analyst at Valera Health from 2015 to 2017. This position involved analyzing data to support health initiatives and improve patient outcomes. His experience in data analysis complements his computational biology work, allowing him to leverage data-driven insights in medical research.