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Benjamin Lacar's work experience includes a role as a Staff Machine Learning Researcher at Seer, where they are involved in developing analysis methods for mass spectrometry datasets and creating go-to-market data content. Benjamin has also worked as a Data Science Health Innovation Fellow at the University of California, San Francisco, where they spearheaded efforts to improve clinical insights and workflows using data science. Additionally, Benjamin has experience as a Data Science Fellow at Insight Data Science, where they built web applications and identified factors associated with low-income high school student success. Prior to that, they worked as a Bioinformatics Scientist and Applications and Data Scientist at Fluidigm Corporation, where they developed analysis pipelines and performed regression analysis for genomic data. Benjamin also has experience as a Postdoctoral Research Associate at the Salk Institute for Biological Studies and as a Graduate Student in Neuroscience at Yale University School of Medicine. Benjamin began their research career as a Research Assistant at UCLA and Lund University.

Benjamin Lacar holds a Ph.D. in neuroscience from Yale University and a Bachelor of Science degree in Biochemistry from UCLA. Benjamin has also obtained several additional certifications, including "Structuring Machine Learning Projects" from Coursera in July 2021, "Intermediate SQL" from DataCamp in October 2020, and "Bayesian Statistics: From Concept to Data Analysis" from Coursera in October 2018. Benjamin has also completed various courses and specializations on topics such as data science, machine learning, deep learning, and programming through platforms like Coursera and Udemy.