Investigador Postdoctoral. Luis studied a degree in Biochemistry in the University of Seville (2017) and a Master’s in Neuroscience at the Autonomous University of Madrid (UAM, 2017-19). He obtained his PhD in Biomedical Research (UCM, 2025), where his work explored how alterations in lipid metabolism, particularly cholesterol, contribute to the pre-symptomatic and early stages of ALS. Now, as postdoctoral researcher, he is focused on applying long-read sequencing technologies to uncover novel genetic factors in ALS. His work involves optimizing bioinformatics tools for variant calling to detect SNPs, SVs, CNVs, repeat expansions, and to perform epigenetic analyses. Outside the lab, Luis enjoys playing sports, watching true crime series, listening to music ranging from Linkin Park to Bad Bunny, and discovering new food spots. SEG 11065: EMBO Scientific Exchange Grant (SEG 11065). Short-term fellowship. Fellow: Luis C. Fernández Beltrán. Stay at Edinburgh Genomics Unit at the University of Edinburgh. September-November 2024
Investigador postdoctoral.
Ayudante de investigación
Karen studied the degree in Human Biology at the Pompeu Fabra University of Barcelona (2019 -2024), and a master´s degree in Neuroscience with a specialization in the clinical field at the Complutense University of Madrid (2024 -2025). Currently, she is a doctoral student in the Biomedical Research program of the Complutense University of Madrid. Her thesis consists in the characterization of a new mouse model with a mutation in the C9ORF72 gene, which is the most commonly mutated gene in patients with familiar amyotrophic lateral sclerosis. Her work is based on carrying out behavioral, motor and methabolic test and the study of molecular and cellular biology of the murine model. Among her hobbies, she enjoys reading novels, traveling, discovering new cultures, and trying new dishes.
Jorge is currently pursuing his PhD in Computer Engineering at UCM, focusing on the intersection of AI applied to omics data obtained through long-read sequencing (Oxford Nanopore Technologies) and graph-based modeling, among other complementary methodologies. His research aims to develop robust and reproducible systems that support decision-making in biomedicine. He holds a degree in Biotechnology from UFV (2020–2024) and a Master’s in Computational Biology from UPM (2024–2025). For his Master’s thesis, he optimized the preparation of gDNA libraries for sequencing with Oxford Nanopore and designed and automated a bioinformatics pipeline for genomic variant analysis. Beyond academia, Jorge enjoys learning languages, exploring music, and being chronically online.
