Professional Career

Daniel earned a Bachelor’s degree in Molecular Sciences, a Pre-Master’s in Artificial Intelligence, and a Master’s degree in Bioinformatics (Cum Laude) from Radboud University. During his studies, he completed internships at Radboudumc, which sparked his interest in computational biology. He began his career as a Data Scientist at Radboudumc (March 2020 – February 2021), focusing on deep learning for computational immunology and personalized vaccine development. He then pursued a PhD at Radboudumc (March 2021 – June 2023), integrating deep learning into bioinformatics, with applications ranging from protein structure analysis to malaria research. After earning his PhD, Daniel worked as a Postdoctoral Researcher at Radboudumc (June 2023 – November 2024), leading projects on neural network representations for molecular modeling, peptide docking, MHC-peptide binding affinity predictions, and therapeutic target development for Usher syndrome. Alongside his research, Daniel developed and led courses for bachelor’s, master’s, and PhD students, focusing on teaching deep learning techniques and their application in scientific fields.