Applications are invited for a full-time, fully funded four-year PhD position at the UCD Cancer Data Lab, University College Dublin, Ireland. The PhD studentship will cover EU tuition fees and a tax-free stipend of €22,000 per year.
Project overview:
Understanding why the mutation of some genes causes phenotypic defects while others are well tolerated is crucial both for understanding the genetic variation observed in human populations and for the development of new therapeutic approaches for inherited disease. Particularly important in this context are gene duplicates (paralogs). Because of their shared origin, pairs of paralogs often perform similar functions and therefore may compensate for each other’s loss. However 80% of Mendelian disease genes have identifiable paralogs. This suggests that the loss of these genes cannot be adequately compensated for by a paralog. The goal of the PhD will be to understand why certain paralogs cause disease when mutated and more generally how paralogs contribute to human genetic robustness. We are particularly interested in integrative/systems approaches to address this.
In recent work we have explored how paralogs influence the response of cancer cells to genetic perturbation (De Kegel and Ryan, PLoS Genetics 2019) and how they shape the evolution of tumour genomes (De Kegel and Ryan, Molecular Systems Biology 2023). We have also explored, using proteomic approaches, how mutation/deletion of one paralog can alter the abundance of another (Venkatesh et al, Biorxiv 2024). This PhD project will move beyond cancer to look at the role of paralogs in inherited diseases.
About us:
We are a supportive and collaborative interdisciplinary research group based in the Conway Institute and associated with the School of Medicine in University College Dublin. We use large-scale data analysis and machine learning approaches to understand the consequences of genetic variation and to identify new therapeutic targets. See cancerdata.ucd.ie/ for more details
Due to the funding source, this position is only available to students from the EU/EEA/UK/Switzerland. This will be a fully dry-lab role and strong data analytics skills are required. Applicants should typically have a primary degree in genetics, bioinformatics, or computer science. If you're not in this category, feel free to send me a mail to discuss.
Expertise in any of the below areas would be a plus:
- machine learning
- network biology
- systems biology
- analysing large scale genetics datasets
- evolutionary biology
Please send an email to Colm Ryan with CV and Cover Letter. Informal enquiries are also welcome.