professor profile picture

Christophe Dessimoz

Prof

SIB Swiss Institute of Bioinformatics

Country flag

Switzerland

Has open position

This profile is automatically generated from trusted academic sources.

Google Scholar

.

ORCID

.

LinkedIn

Social connections

How do I reach out?

Sign in for free to see their profile details and contact information.

Meet Kite AI

Contact this professor

LinkedIn
ORCID
Google Scholar

Research Interests

Statistics

10%

Artificial Intelligence

10%

Comparative Genomics

10%

Biology

10%

Machine Learning

10%

Agriculture

10%

Bioinformatic

10%

Ask ApplyKite AI

Start chatting
How can you help me contact this professor?
What are this professor's research interests?
How should I write an email to this professor?

Positions1

Publisher
source

Natasha Glover

University Name
.

SIB Swiss Institute of Bioinformatics

Research Scientist in Computational Comparative Genomics, Protein Structure, and AI for Crop Improvement

Research Scientist opening in computational comparative genomics, protein structure, and AI for crop improvement at the SIB Swiss Institute of Bioinformatics and the University of Lausanne in Lausanne, Switzerland. The position is part of the SNSF-funded AI-driven Comparative QTLomics project, a collaborative effort involving researchers in Switzerland and Denmark. The project aims to combine comparative genomics , orthology inference , protein evolution , protein structure , synteny , machine learning , and AI-assisted literature mining to improve candidate gene prioritisation and accelerate crop improvement across plant species. The successful candidate will develop and benchmark methods for HOG/orthology inference in plants, integrate protein structure information into the OMA workflow, work with large-scale plant genome datasets, build benchmark gene-family datasets, and explore ML approaches that combine sequence, structure, synteny, and phylogenetic evidence. The role also includes open-source software development, reproducible workflows, and publication of results. Applicants should have a PhD in computational biology, bioinformatics, evolutionary genomics, structural bioinformatics, computer science, or a related field. Strong Python programming, Linux/HPC experience, reproducible computational workflows, and experience with large biological datasets are expected. Experience in comparative genomics, phylogenomics, orthology, protein structure, synteny, or AI/ML for biological data is highly relevant. Plant biology experience is welcome but not required. To apply, submit your application through the online portal with a CV, motivation letter, and contact details for 2-3 referees.