Christoph Brunken
About Christoph Brunken
Christoph Brunken is a Research Engineer at InstaDeep, specializing in Geometric Deep Learning for protein and small molecule structural information. He holds a PhD in Theoretical Chemistry from ETH Zürich and has experience in data engineering and AI research in drug discovery.
Work at InstaDeep
Christoph Brunken currently holds the position of Research Engineer at InstaDeep Ltd, a role he has occupied since 2023. His work focuses on applying Geometric Deep Learning techniques to analyze structural information of proteins and small molecules. This application is significant in advancing research in drug discovery and biotechnology. He utilizes machine learning engineering within the JAX ecosystem to enhance research methodologies in these fields.
Education and Expertise
Christoph Brunken has a robust academic background, having studied at prestigious institutions. He earned a Doctor of Philosophy (PhD) in Theoretical Chemistry from ETH Zürich, where he conducted research from 2017 to 2021. Prior to this, he completed a Master of Science (MS) in Chemistry at Heidelberg University from 2015 to 2017, following a Bachelor of Science (BS) in the same field from 2012 to 2015. His education has equipped him with a deep understanding of chemical principles and advanced computational techniques.
Background
Before joining InstaDeep, Christoph Brunken worked as a Data Engineer at Zühlke Group from 2021 to 2023 in Zürich, Switzerland. He also served as a Doctoral Student at ETH Zürich from 2017 to 2021, where he focused on developing methods to improve protein modeling and computer-assisted drug discovery. His diverse experiences in both academic and industry settings contribute to his expertise in the intersection of chemistry and artificial intelligence.
Achievements
During his PhD studies at ETH Zürich, Christoph Brunken developed innovative methods aimed at enhancing research in protein modeling and computer-assisted drug discovery. His work involved utilizing machine learning engineering techniques, particularly within the JAX ecosystem, to support advancements in drug discovery and biotechnology. These contributions reflect his commitment to integrating computational approaches within the life sciences.