Grégoire André
About Grégoire André
Grégoire André is a Machine Learning Developer with expertise in Matlab and Python, focusing on experimental data analysis. He has a strong background in computational sciences and currently works at SOPHiA GENETICS and serves as a Teaching Assistant at Ecole polytechnique fédérale de Lausanne.
Work at SOPHiA GENETICS
Grégoire André has been employed as a Machine Learning Developer at SOPHiA GENETICS since 2019. His role involves investigating the application of deep convolutional neural networks for variant calling. This position allows him to leverage his expertise in machine learning and data analysis within the context of genomic data.
Education and Expertise
Grégoire André holds a Master's degree in Applied Physics and a Bachelor's degree in Physics from Ecole polytechnique fédérale de Lausanne. His academic background provided him with a strong foundation in mathematical and computational sciences, which he applies in his current work. He possesses strong skills in Matlab and Python, particularly in experimental data analysis.
Background
Grégoire André began his academic journey at Lycée Sainte-Croix de Neuilly, where he achieved the French Baccalauréat S with honors. He then pursued his studies at Ecole polytechnique fédérale de Lausanne, completing both his Bachelor's and Master's degrees in Physics and Applied Physics, respectively. His interest in computational sciences developed during this time.
Previous Experience
Prior to his current roles, Grégoire André worked as a Computer Vision Engineering Intern at Logitech for six months in 2018. He also completed a Master Project at LASTRO (EPFL Astrophysics Lab) for five months, where he focused on machine learning techniques applied to astrophysical data. Additionally, he has served as a Teaching Assistant at Ecole polytechnique fédérale de Lausanne since 2016.
Skills and Competencies
Grégoire André has developed strong teamworking and communication skills through various professional and associative experiences. His technical skills include proficiency in Matlab and Python, particularly in the context of experimental data analysis. His background in physics and machine learning enhances his ability to tackle complex problems in computational sciences.