I pursued my undergraduate studies at Leiden University, where I completed a Bachelor of Science in Bio-Pharmaceutical Sciences. It was during this program that I was first introduced to the fascinating field of computational drug discovery. Motivated by this initial exposure, I decided to pursue a Master's degree in Bio-Pharmaceutical Sciences at Leiden University as well. During my master's program, I had the opportunity to delve deeper into the field of computational drug discovery through my research projects. In my first project, I joined the Computational Drug Discovery group at the Leiden Academic Centre for Drug Research (LACDR). Under the guidance of Marina Gorostiola González, I focused on extracting three-dimensional dynamic protein descriptors (3DDPDs) from molecular dynamics (MD) simulations. This research provided me with a comprehensive understanding of both the dynamic aspects of protein behavior and the intricacies of machine learning in drug design and analysis. Seeking further knowledge and experience, I embarked on a second research project at the Computational Biology and Bioinformatics group in Uppsala, Sweden. Here, under the supervision of Hugo Gutiérrez de Teran, I worked on PyMemDyn, a pipeline designed for membrane protein embedding and MD simulations. This project not only enhanced my expertise in computational methods and software development but also provided me with valuable insights into the challenges and intricacies of studying membrane proteins. Through these research experiences, I developed a strong toolkit encompassing both machine learning and structure-based drug discovery approaches. Armed with this knowledge, I am now eager to embark on a Ph.D. journey focused on de novo drug development, with a particular emphasis on expanding upon the DrugEx framework. By combining my computational expertise with innovative approaches in drug design, I aim to contribute to the development of novel therapeutics that can address unmet medical needs. Now, I am excited to apply this knowledge and continue pushing the boundaries of drug development during my Ph.D. track. Orchid ID 0009-0008-5661-1157

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