Role overview
Cancer is a genetic disease, subject to population genetics forces like mutation, selection and stochasticity. Our group is particularly interested in how the evolution and survival of cancer cell populations relies on mutation influx and in how cancer driver events can be identified from observed mutation data. To this end, we develop mathematical and computational approaches to estimate mutation rates, tumor growth dynamics and selection. Analysis of the mutational processes acting in cancer genomes allows us to learn about carcinogenic mutagens (https://www.biorxiv.org/content/10.1101/2023.12.06.570467v1), while studying the spatial genetic heterogeneity of tumors tells us about the tumor mode of growth (https://elifesciences.org/reviewed-preprints/95338). Estimates of the strength of selection in cancer allow a prioritization of genes and non-coding regions by their disease relevance, with the ultimate goal of promoting therapeutic advances. Coding sequences of cancer tumors not only exhibit positively selected mutations that drive cancer (www.nature.com/articles/s41588-019-0572-y), but also a small fraction of genes that the tumor cannot afford to lose (www.nature.com/articles/ng.3987). In addition to genes, cancer driver loci can occur in the non-coding part of the genome (www.nature.com/articles/s41467-017-00100-x).
We are also interested in mutation rates and selection inference in the context of human genetic variation, including from single-nucleotide polymorphisms (https://www.nature.com/articles/s41467-025-66201-0; http://www.nature.com/articles/ng.3831; academic.oup.com/mbe/article-abstract/36/8/1701/5475505) and de novo variants (www.nature.com/articles/s41467-020-17162-z). Here, a particular focus of the group lies on the description of purifying selection in humans and across species, accounting for mutational processes as well as the effects of genetic drift.
The Evolutionary Processes Modeling lab was established in October 2018 and is part of the “Computational Biology and Health Genomics” program at the CRG. Further information can be found at https://weghornlab.org/ and at www.crg.eu/en/programmes-groups/weghorn-lab.
*Whom would we like to hire?
Professional experience
What we're looking for
- Experience with computational data analysis
- Familiar with modeling and statistical analysis
- Contract duration: Technical and scientific activities contract (estimated duration until September 2027).
- Estimated annual gross salary: Salary is commensurate with qualifications and consistent with our pay scales.
- Target start date: April 2026.
We provide a highly stimulating environment with state-of-the-art infrastructure and unique professional career development opportunities. To check out our training and development portfolio, please visit our website in the training section.
We offer and promote a diverse and inclusive environment and welcome applicants regardless of age, disability, gender, nationality, ethnicity, religion, sexual orientation or gender identity.
The CRG is committed to reconcile a work and family life of its employees and is offering extended vacation periods and the possibility to benefit from flexible working hours.