Ximun Loyatho
About Ximun Loyatho
Ximun Loyatho is a Software Engineer at SOPHiA GENETICS in Bidart, France, specializing in bioinformatics and genomics with expertise in parallel computing and performance optimization. He has a strong educational background in mathematics and engineering, having studied at prestigious institutions and worked in various roles at Dassault Aviation.
Work at SOPHiA GENETICS
Ximun Loyatho has been employed as a Software Engineer at SOPHiA GENETICS since 2019. Located in Bidart, Nouvelle-Aquitaine, France, he has contributed to the company's initiatives for five years. His role involves working on software solutions that enhance bioinformatics and genomics, particularly in the context of next-generation sequencing technologies. Loyatho is also engaged in software maintenance and testing processes, focusing on high code quality and efficient release cycles.
Education and Expertise
Ximun Loyatho holds a Master 2 (M2) degree in Numerical Analysis & Partial Differential Equations, Mathematics and Applications from Université Pierre et Marie Curie, which he completed from 2011 to 2012. He also earned a Diplôme d'ingénieur in Mathématiques appliquées from ENSTA ParisTech - École Nationale Supérieure de Techniques Avancées, studying from 2009 to 2012. His educational background is complemented by his expertise in parallel computing and performance optimization within Unix environments.
Background
Prior to his current role at SOPHiA GENETICS, Ximun Loyatho worked at Dassault Aviation in various capacities. He began as a Simulation numérique électromagnétique for six months in 2012, followed by a seven-year tenure as Ingénieur conception R&D from 2012 to 2019. Both positions were based in Saint-Cloud, Île-de-France, France, where he gained experience in engineering and software development.
Specialization in Bioinformatics
Ximun Loyatho specializes in bioinformatics and genomics, focusing on next-generation sequencing technologies. His work involves developing software solutions that support genomic analysis and data interpretation, contributing to advancements in the field of personalized medicine and genetic research.