PhD Fellowship: Cross-Species Regulatory Genomics & AI

Technical Sciences - Center for Kvantitativ Geneti; Aarhus; On-site; DKK 357,000 - 402,000; Full time

Job summary

Aarhus University invites applications for a PhD fellowship in the Quantitative Genetics and Genomics programme. The project aims to decipher regulatory logic through cross-species analysis of the regulatory genome, leveraging AI frameworks to identify functional variants across species.

The successful candidate will join a high-impact, international research group, work with large multi-omics datasets, and contribute to manuscripts published in premier journals.

Qualifications

• Master’s degree in Statistical Genetics, Bioinformatics, Computational Biology, Computer Science, Mathematics, or closely related quantitative field.
• Proficiency in Python or R for genomic algorithms.
• Experience with machine learning or deep learning frameworks (e.g., PyTorch, TensorFlow) is desirable.
• Strong interest in human/animal genetics or comparative genomics.

Responsibilities

• Develop novel AI frameworks to identify functional genetic variants influencing gene regulation across species.
• Perform cross-species comparative analyses of regulatory patterns in farmed animals and humans.
• Map regulatory mechanisms to complex traits to improve predictive accuracy in clinical and agricultural settings.
• Contribute to drafting high-impact manuscripts and collaborate in international consortia.

Skills

Analytical thinking

Team collaboration

Scientific writing

Education

Master's degree in Statistical Genetics or closely related field

Tools

Python

R

PyTorch

TensorFlow

Job description

Aarhus University invites applications for a PhD fellowship in the Quantitative Genetics and Genomics programme. The project aims to decipher regulatory logic through cross-species analysis of the regulatory genome, leveraging AI frameworks to identify functional variants across species.

The successful candidate will join a high-impact, international research group, work with large multi-omics datasets, and contribute to manuscripts published in premier journals.