Jon Frias holds a Biomedical Sciences degree from the University of Barcelona (UB, 2015) and a master’s degree in Statistics and Operative Research from the Polytechnic University of Catalonia (UPC, 2017). He centered his career in the fields of Biostatistics and Bioinformatics.

For his bachelor’s thesis, he joined Josefa Gonzalez’s lab at the Institute of Evolutionary Biology (IEB) from November 2014 to July 2015. His research focused on the role of the juvenile hormone epoxide hydrolase during the juvenile hormone catabolism in Drosophila melanogaster. During this stage, he also took a postgraduate course on Evolutionary Biology organized by the Outreach and Training Unit of the IEB (CISC-UPF).

In 2016, he attended a research summer school in statistical omics in Split, Croatia. Thereafter, he joined the Cancer Epidemiology Research Programme (PREC) for his master thesis, doing statistical analysis in studies of HPV and head and neck cancers. In 2018, he joined Laura Costas’s team under a fellowship from the Health Department of the Government of Catalonia (PERIS fellowship) to conduct statistical analysis on endometrial and ovarian cancer research and to pursue a PhD in medicine. In 2019, he enrolled as PhD student at the University of Barcelona to start his predoctoral stage in medicine and translational research, in the field of cancer and human molecular genetics. In 2019, he also obtained a fellowship from the national Institute of Health Carlos III (PFIS fellowship) to continue his PhD research from 2021 to 2024.

Currently, he works under Laura Costas’s supervision at the Screenwide team, which aims to find a molecular signature for the early detection of endometrial and ovarian cancers. He also works with the National Cancer Institute on machine-learning techniques to predict endometrial cancer risk based on clinical, molecular and epidemiological data. Moreover, he collaborates with the Epidemiology of Endometrial Cancer Consortium (E2C2) in studying the potential risk factors of night shifts and sleep duration patterns in the development of endometrial cancer.