Eduardo Soto
About Eduardo Soto
Eduardo Soto is a Pew Latin American Postdoctoral Fellow in the Biomedical Sciences at Yale University, specializing in microbiology, synthetic biology, bioinformatics, and omics sciences. He holds multiple degrees from Universidad Nacional Autónoma de México, including doctorates in Molecular Biology and Biochemistry.
Work at Yale University
Eduardo Soto has been serving as the Pew Latin American Postdoctoral Fellow in the Biomedical Sciences at Yale University since 2017. His role involves conducting research that integrates bioinformatics with experimental data to uncover new biological insights. Yale University, located in New Haven, Connecticut, is recognized for its commitment to advancing knowledge in the biomedical field, and Soto's contributions align with this mission.
Education and Expertise
Eduardo Soto obtained his Doctor of Philosophy degree from Universidad Nacional Autónoma de México, where he studied Molecular Biology, Biochemistry, and Philosophy from 2012 to 2016. He also earned a Master's degree in Molecular Biology and Biochemistry from 2010 to 2012. His academic background is complemented by a Bachelor's degree in Genomics, which he completed from 2006 to 2010. Soto specializes in microbiology, synthetic biology, bioinformatics, and omics sciences.
Background in Teaching and Research
Prior to his current position, Eduardo Soto worked as a PhD student at Instituto de Fisiología Celular from 2012 to 2017. He also gained teaching experience as a Systems Biology Teaching Assistant and a Linear Algebra Teaching Assistant at Centro de Ciencias Genómicas - UNAM in 2009 and 2010, respectively. These roles provided him with a solid foundation in both teaching and research methodologies.
Technical Skills and Programming Experience
Eduardo Soto possesses extensive experience with Linux operating systems and is proficient in several programming languages, including Perl, R, and MATLAB. He has expertise in managing relational databases and SQL, which supports his research in bioinformatics and data analysis. His technical skills enable him to effectively combine computational predictions with experimental findings.