Anders Rasmussen
About Anders Rasmussen
Anders Rasmussen is an Associate Computational Biologist II at the Broad Institute of MIT and Harvard, specializing in the integration of machine learning techniques with genomics research. He has a background in mathematics and mechanical engineering from MIT and has worked in various roles in computational biology and software engineering.
Work at Broad Institute
Anders Rasmussen has been serving as an Associate Computational Biologist II at the Broad Institute of MIT and Harvard since 2022. In this role, he is involved in research that focuses on the 4D Nucleome, which aims to understand the three-dimensional organization of the nucleus in space and time. His work contributes to the institute's mission of advancing genomic research through innovative computational methods.
Previous Experience in Computational Biology
Prior to his current position, Anders Rasmussen worked at the Simons Foundation as a Software Engineer from 2021 to 2022. He also held the role of Associate Software Engineer at the same foundation from 2017 to 2021. Additionally, he served as a Visiting Scientist in Maniatis' Lab at Columbia University from 2021 to 2022. His experience in these roles has provided him with a strong foundation in software development and computational biology.
Education and Expertise
Anders Rasmussen earned a Bachelor of Science degree in Mathematics and Mechanical Engineering from MIT, where he studied from 2010 to 2016. His academic background supports his specialization in integrating machine learning techniques with genomics research. He also possesses expertise in Bayesian statistics and numerical simulation, which are critical for advancements in areas such as CRISPR and epigenomics.
Early Career Background
Anders Rasmussen began his career as a Portfolio Tool Developer at SCS Financial in 2014, where he worked for a brief period of three months in Boston, MA. This early experience in financial technology provided him with insights into software development before transitioning to computational biology roles.