The Animal Genomics group at the Institute of Agricultural Sciences at ETH Zurich investigates DNA variation in individual genomes and at the population scale. We apply long read sequencing technologies to characterize animal genomes, and use bioinformatics and statistical genomics approaches to identify trait-associated sequence variation. We offer a PhD position at the interface of computational and statistical genomics, and bioinformatics.
Cattle are an interesting «model organism» to study inherited genetic variation and the molecular-genetic underpinnings of complex traits and diseases. Whole-genome sequencing and dense phenotyping data are available for tens of thousands of individuals. These data enable studying the transmission of alleles and powerful association testing to understand the genetic architecture of complex traits and diseases.
The project «OPISCOW - Origin, prevalence, and impact of complex structural variation in a large mammalian genome discovered through genome assembly at the population scale» is a 4-year project recently funded by the Swiss National Science Foundation (SNSF). OPISCOW aims to investigate the de novo mutation rate of structural variants in a large cattle pedigree using highly accurate long reads and near-complete assemblies.
We are seeking an enthusiastic and highly motivated candidate to investigate long read sequencing data collected from a large cattle pedigree. HiFi data will be available for 50 trios (mother, father, offspring). The PhD student will be responsible for (a) mapping these reads against a recently built T2T assembly, and (b) creating haplotype-resolved assemblies for the offspring animals. Both read alignments and assemblies will be analyzed to identify variants in the offspring not present in both parental genomes, enabling the study of de novo variant occurrence. There is also an opportunity to contribute to our ongoing effort to establish a comprehensive bovine pangenome.
Preferred experience includes workflow management software (e.g., Snakemake or Nextflow), genomic data analysis on high-performance computing clusters, and strong communication skills.
Profile
* Research interest in statistical genomics, computational biology, computational genomics, or animal genomics
* Experience with programming languages (e.g., Python, R) and basic knowledge of high-performance computing clusters
* A MSc degree in genomics, computational biology, bioinformatics, genetics, animal sciences, or related disciplines
* Strong interest in computational genomics, bioinformatics, or statistics
* Proficiency in scientific writing and participation in international conferences, with good command of English
We offer
An inspiring, supportive, and collaborative research environment within a fully funded 4-year project. Our team is young, international, and has a strong publication record. We offer:
* Integration into a dynamic research team with diverse backgrounds
* Responsibility for conducting research within a funded project
* High level of support throughout the PhD journey
* Flexibility to develop and pursue individual research ideas within the project scope
* Opportunities for collaboration with national and international partners
* Participation in conferences and seminars
ETH Zurich promotes an inclusive culture, equality, diversity, and a respectful working environment. Visit our Equal Opportunities and Diversity webpage for more information.
Application details
This is a fixed-term position for 4 years, starting ideally on October 1st, 2025 (negotiable). Some data collection has already been completed, allowing for an earlier start. You will join the Animal Genomics group led by Prof. Hubert Pausch.
We look forward to your online application including:
* A motivation letter demonstrating your suitability and research interests
* A comprehensive CV with academic records and copies of degrees
* Contact details for two references
Application review begins June 15th and continues until the position is filled. Applications via email or postal mail will not be considered. For questions, visit our website or contact Prof. Hubert Pausch at hubert.pausch@usys.ethz.ch (please note, no applications via email).
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