Research Scientist Position in Comparative Genomics
A Research Scientist position is available in the Comparative Genomics group led by Dr. Natasha Glover and Prof. Christophe Dessimoz at the SIB Swiss Institute of Bioinformatics / University of Lausanne.
Plant genomes present significant challenges for orthology inference, including high duplication rates, gene family expansion, genome rearrangements, hybridization, introgression, and variable annotation quality. The successful candidate will develop and benchmark new approaches to enhance HOG inference by integrating additional sources of evidence, particularly protein structure and synteny.
Responsibilities
The Research Scientist will be expected to:
- Develop methods to improve orthology reconstruction and HOG inference in plants.
- Integrate protein structure information into the OMA orthology inference workflow to enhance deep homology detection and refine HOGs.
- Perform large-scale orthology inference and benchmarking on plant datasets, including genome collection, quality control, species tree inference, and FastOMA-based HOG reconstruction.
- Build or assemble benchmark datasets of curated plant gene families, including cases with duplications and broad taxonomic sampling.
- Evaluate methodological improvements using both curated gene family benchmarks and large-scale reference-free metrics, such as HOG completeness, ancestral gene repertoire size, duplication patterns, and consistency across taxonomic levels.
- Explore the use of machine learning to combine sequence, structure, synteny, and phylogenetic information for improved homology and orthology inference.
- Develop reusable, open-source software and workflows to be made available through the group’s GitHub repositories.
- Prepare results for publication in peer-reviewed scientific journals.
- Contribute to the broader Comparative QTLomics consortium, aiming to enhance candidate gene prioritization through AI-assisted QTL extraction, comparative evolutionary genomics, and functional data integration.
The exact methodological direction will be shaped collaboratively with the candidate, depending on their expertise. The successful candidate will work closely with an interdisciplinary team on the SNSF-funded project AI-driven Comparative QTLomics to accelerate crop improvement. This project aims to integrate AI-assisted literature mining, orthology inference, comparative genomics, co-evolution, co-expression, and functional data. Collaborators include researchers from SIB, the University of Lausanne, Aarhus University, and Aalborg University.
Profile Requirements
Applicants should have:
- A PhD in computational biology, bioinformatics, evolutionary genomics, structural bioinformatics, computer science, or a related field.
- Strong programming skills, preferably in Python.
- Experience working in Linux and HPC environments.
- Experience with reproducible computational workflows and large-scale biological datasets.
- A strong interest in method development for comparative genomics, evolutionary biology, or biological data integration.
Applicants should also possess expertise in one or more of the following areas:
- Comparative genomics or evolutionary genomics.
- Orthology inference or gene family reconstruction.
- Structural bioinformatics or protein structure analysis.
- Synteny analysis or genome evolution.
- Phylogenetics or phylogenomics.
- Machine learning or AI applied to biological data.
Experience with Linux, Python, HPC environments, and reproducible computational workflows is expected. Prior experience with plant biology is desired but not required, and we strongly encourage applications from candidates with transferable computational or methodological expertise from adjacent fields.
What We Offer
- An interdisciplinary and collaborative research environment at SIB and UNIL.
- The opportunity to develop new methods in comparative genomics, orthology inference, and AI-assisted biological data integration.
- Access to large-scale genomic, phylogenomic, and protein structure datasets.
- Collaboration opportunities with UniProt and international plant genomics groups.
- Possibilities for international collaborations and research exchanges.
- A flexible project with room for independent methodological development.
The position is hosted within the Comparative Genomics Group at SIB in Lausanne, Switzerland, which develops widely used comparative genomics resources and methods including OMA, FastOMA, OMArk, HOGProf, and related tools. Apply online using the form below. Only applications matching the job profile will be considered.