Postdoctoral Position in Plant Evolutionary Genomics and Pangenomics

SLU - Swedish University of Agricultural Sciences

Uppsala, Sweden

About the position

A postdoctoral position in plant evolutionary genomics is available in the Yant Lab at the Swedish University of Agricultural Sciences (SLU) in Uppsala, Sweden. The Yant Lab develops computational and genomic approaches to understand evolution, adaptation, genome dynamics, and whole-genome duplication across diverse plant systems.

The project is funded through a Formas grant aimed at restoring European ash (Fraxinus excelsior) populations threatened by ash dieback. The successful candidate will contribute to developing the first Swedish-focused European ash pangenome, integrating long-read genome assemblies with population-scale sequencing to understand disease resistance and local adaptation across Europe.

The project combines large-scale population genomics, graph-based pangenomics, structural variant discovery, genome-wide association studies, and evolutionary genomics using state-of-the-art long-read sequencing and computational genomic approaches. The successful candidate will work closely with collaborators at other SLU campuses, the Royal Botanic Gardens, Kew, and other European partners, contributing to both methodological developments and biological discovery.

The project offers an opportunity to work at the forefront of plant evolutionary genomics while contributing directly to forest restoration and conservation.

Your profile

We are looking for a highly motivated candidate with a PhD in botany, evolutionary biology, genetics, genomics, bioinformatics, plant biology, or a related subject deemed equivalent by the employer. The applicant should have a strong publication record relative to career stage and demonstrated ability to conduct independent research. The ideal candidate will have experience in all of the following areas:

• large scale population genomics, demographic inference, and evolutionary genomics;
• graph-based pangenomics and structural variant analysis, ideally in plants;
• genotype-environment association (GEA/EAA) or GWAS;
• programming in Python, with extensive experience working in Linux and multiple HPC environments;
• population genomics across environmental gradients, including demographic inference and genotype–environment association analyses.

Experience with long-read sequencing, structural variant analysis, graph-based genome analysis, and plant genomics is considered an advantage but is not required.

The successful candidate is expected to be a collaborative team member who will drive the project with creativity, independence, and scientific curiosity. Excellent written and spoken English is required.

Since postdoctoral appointments are career-development positions, priority will be given to candidates who received their doctoral degree within the past three years.