Summary
Aarhus University is inviting applications for a PhD fellowship in Comparative Genomics and Machine Learning within the Quantitative Genetics and Genomics programme. The scholarship aims to develop computational tools to prioritize candidate genes, enhancing modern plant breeding through evolutionary and functional information integration.
PhD Candidate in Comparative Genomics and Machine Learning for Plant Biology, Denmark
Designation
PhD Candidate
Research Area
Comparative Genomics, Machine Learning, Plant Biology
Location
C.F. Møllers Allé 3, Bldg. 1130, 8000 Aarhus C, Denmark
Eligibility/Qualification
- Master’s degree in Bioinformatics, Computational Biology, Computer Science, Mathematics, Physics, or a related field.
- Knowledge of programming in Python or R.
- Familiarity with machine learning or deep learning methods is advantageous.
- Interest in plant genomics, evolutionary biology, or comparative genomics.
- Proficient in written and spoken English communication skills.
Job Description
The selected candidate will focus on three main objectives:
- Develop an algorithm that integrates evolutionary and functional information using comparative genomics and deep learning approaches.
- Apply this framework across the plant kingdom to identify patterns of gene redundancy and pleiotropy.
- Identify genes associated with key agronomic traits, such as flowering time and root architecture.
This project offers an opportunity to gain skills in comparative genomics, phylogenomics, and deep learning while contributing to computational approaches that support crop improvement.
How to Apply
Interested candidates should submit their application via the provided link under ‘how to apply.’ A project description (copied from the announcement) must be uploaded as a PDF.
Last Date for Application
31 May 2026, 23:59 CEST
Contact Information
For further inquiries, please contact:
- Professor Torben Ask
Email: torben.asp@qgg.au.dk
Phone: +45 8715 8243 - Assistant Professor Irene Julca
Email: irene.julca@qgg.au.dk
Aarhus University welcomes applications from all individuals and values diversity.







