Applicants are invited for a PhD fellowship/scholarship at the Graduate School of Technical Sciences, Aarhus University, Denmark, within the Quantitative Genetics and Genomics programme. The position is available from 01 October 2026 or as soon as possible thereafter. You can submit your application via the link under 'how to apply'.
Understanding when genes are functionally redundant or influence multiple traits (pleiotropy) is important for accelerating modern plant breeding. This project aims to develop computational tools, including deep learning and AI, to prioritise candidate genes by integrating evolutionary and functional information.
The selected candidate will work on three main objectives:
1. Develop an algorithm that integrates evolution and functional information using comparative genomics and deep learning approaches.
2. Apply this framework across the plant kingdom to identify conserved patterns of gene redundancy and pleiotropy.
3. Identify genes associated with key agronomic traits, such as flowering time and root architecture.
This project will provide the PhD student with the opportunity to develop skills in comparative genomics, phylogenomics, and deep learning, while contributing to computational approaches that support crop improvement.
Applicants to the position must hold a Master’s degree in Bioinformatics, Computational Biology, Computer Science, Mathematics, Physics, or a related field, and:
- Knowledge in programming in Python or R
- Familiarity with machine learning or deep learning methods is a plus
- Interest in plant genomics, evolutionary biology, or comparative genomics
- Proficient in written and spoken English communication skills
Please follow the instructions in this link: app.researchplanner.net/Peoplexs22/CandidatesPortalNoLogin/ApplicationForm.cfm?PortalID=16581&VacatureID=1083780