Peder Lyngby is a Staff R&D Engineer at Synopsys QuantumATK, where they build atomic-scale simulation tools and leverage AI for materials innovation. Peder holds a PhD in machine learning for atomistic materials discovery from DTU - Technical University of Denmark, complemented by a Bachelor's and Master's degree in Physics and Nanotechnology from the same institution. Prior to their current role, they contributed to academia as a PhD student at DTU Physics, published seven scientific papers, and served as a teaching assistant and lecturer, positively impacting a significant number of students. Furthermore, Peder completed an external stay at the Department of Chemistry, UCPH, focusing on cheminformatics and explainable AI.
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