Project Description

As forests increasingly face challenges brought on by a rapidly changing environment, it is important to address these problems from multiple angles. There is growing awareness of the potential usefulness of genetic data in forest management, but much is unknown about the genomics of non-model plant species like many forest trees.

The McEvoy Lab draws from a variety of new approaches to develop a better understanding of how genomic diversity is distributed in forest tree species, how it has evolved, and implications for the future. Methods range from studying genomic characteristics that drive genome evolution, examining variation critical for survival and fitness such as enhanced disease resistance, assessing and characterizing genetic diversity and population dynamics, and demonstrating how this information can be used to help inform conservation or breeding programs.

Why This Scholarship Stands Out

This PhD is unique because it focuses on the genomics of non-model forest tree species – a field with significant knowledge gaps but growing practical applications for forest management and conservation. The work is primarily computational, requiring development of skills in bioinformatics, population genetics, and large dataset analysis. UPSC is one of Europe’s leading plant research centres, providing access to high-performance computing resources and an international research environment. For a student interested in evolutionary genomics and conservation, this is an opportunity to generate knowledge that can directly inform forest management and breeding programs in Sweden and beyond. The project offers flexibility to explore various questions within forest tree genomics, from genome evolution to disease resistance to population dynamics.

Candidate Profile and Eligibility

My Application Strategy

1. Highlight your computational biology experience – Mention any work with genomic data, bioinformatics pipelines, or programming (Python, R, bash)
2. Emphasize population genetics or evolution coursework – Theory of population genetics, molecular evolution, or phylogenetics
3. Show technical skills – Experience with git, HPC clusters, or workflow management (Snakemake, Nextflow) is valuable
4. Demonstrate ability to synthesize literature – The project requires reviewing and synthesizing scientific concepts
5. Read Dr. McEvoy’s recent publications – Cite their work in your application to show genuine interest

What They Offer

Who Should Apply

This PhD is perfect for a student with a background in evolution, ecology, or plant sciences who wants to develop computational genomics skills. If you are interested in how genomic diversity is distributed across forest tree populations, how it evolves, and how genetic data can inform conservation and breeding, this project offers training in bioinformatics, population genetics, and large-scale data analysis. Candidates with experience in genomic data analysis are especially encouraged. The ideal candidate is someone who enjoys coding, working with large datasets, and applying computational methods to answer biological questions.

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