Job Opportunity: Research Scientist
A Research Scientist position is available in the Comparative Genomics group of 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 innovative approaches to enhance HOG inference by integrating additional evidence sources, especially protein structure and synteny.
Key Responsibilities
- Develop methods to improve orthology reconstruction and HOG inference in plants.
- Integrate protein structure information into the OMA orthology inference workflow, aiming to enhance deep homology detection and refine HOGs.
- Conduct large-scale orthology inference and benchmarking on plant datasets, encompassing genome collection, quality control, species tree inference, and FastOMA-based HOG reconstruction.
- Construct or assemble benchmark datasets of curated plant gene families, including cases with duplications and broad taxonomic sampling.
- Evaluate methodological improvements utilizing 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.
- Investigate how machine learning can be leveraged to consolidate sequence, structure, synteny, and phylogenetic information for enhanced homology and orthology inference.
- Develop reusable, open-source software and workflows, which will be made accessible through the group’s GitHub repositories.
- Prepare results for publication in peer-reviewed scientific journals.
- Contribute to the broader Comparative QTLomics consortium, aimed at improving candidate gene prioritization by combining AI-assisted QTL extraction from the literature, comparative evolutionary genomics, and functional data integration.
The exact methodological direction will be defined collaboratively with the candidate, based 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 integrates AI-assisted literature mining, orthology inference, comparative genomics, co-evolution, co-expression, and functional data to foster crop enhancement across species. Collaborators include researchers from SIB, the University of Lausanne, Aarhus University, and Aalborg University.
Profile Requirements
Applicants should possess:
- 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 keen interest in method development for comparative genomics, evolutionary biology, or biological data integration.
Applicants should also have 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 applications in biological data.
Prior experience with plant biology is desirable but not mandatory. 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 innovative methods in comparative genomics, orthology inference, and AI-assisted biological data integration.
- Access to extensive 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 scope for independent methodological development.
The position will be 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.