PhD Position in Long-Read Computational Genomics

Contribute to the design, development, benchmarking, and maintenance of a comprehensive long-read sequencing analysis pipeline. Perform alignment and variant calling from PacBio HiFi data, including SNVs, indels, structural variants, CNVs, and CpG methylation profiling. Develop and implement telomere-to-telomere (T2T) de novo genome assembly workflows and contribute to the construction of a population-specific reference panel. Establish imputation frameworks to recover genotypes from low-coverage short-read whole-genome sequencing data. Integrate artificial intelligence and machine-learning approaches into variant annotation and interpretation workflows. Conduct statistical genomics analyses, including polygenic risk score development and genetic association studies. Contribute to the analysis of diverse genomic and phenotypic datasets within an international research consortium.

The Centre Hospitalier Universitaire Vaudois (CHUV) is one of the five Swiss university hospitals and a leading center for clinical care, biomedical research, and academic training. Through its close collaboration with the University of Lausanne (Faculty of Biology and Medicine) and the École Polytechnique Fédérale de Lausanne (EPFL), the CHUV offers a highly dynamic and interdisciplinary research environment at the interface of medicine, genetics, and systems biology.

• Master’s degree (or equivalent) in Bioinformatics, Computational Biology, Computer Science, Statistics, Genomics, Genetics, Molecular Biology, Cellular Biology, or a related field.

• Strong programming skills in Python and R.

• Proficiency in Linux environments and high-performance computing (HPC) systems.

• Experience in sequencing data analysis; familiarity with long-read sequencing technologies, statistical genetics, or machine learning is an asset.

• Previous experience in human genetics and/or rare disease genomics is desirable.

• Experience in stem cell biology, including iPSC derivation and differentiation, is an advantage.

• Strong organizational skills, scientific rigor, and attention to detail.

• Ability to work independently while contributing effectively to a collaborative and multidisciplinary international team.

• Excellent written and spoken English; knowledge of French is an asset.