Postdoctoral research in plant regulatory genomics and artificial intelligence

THE SOCIETY FOR EXPERIMENTAL BIOLOGY; Aarhus; On-site; DKK 320,000 - 460,000; Full time

Job summary

The Center for Quantitative Genetics and Genomics (QGG) at Aarhus University invites applications for a postdoctoral position in plant regulatory genomics and artificial intelligence. You will design sequence-to-expression deep learning models to predict gene expression from DNA in plants and will spend 6–12 months at Cold Spring Harbor Laboratory, integrating plant genomics with AI expertise.

The role focuses on data science and regulatory genomics in a model plant species, with a 2‑year

Qualifications

• PhD in computer science, bioinformatics, or related field.
• Experience in deep learning and AI for genomics.
• Publications in peer‑reviewed journals on AI/genomics.

Responsibilities

• Design sequence-to-expression deep learning models to predict plant gene expression from DNA sequences.
• Collaborate with Koo lab at CSHL and leverage new training data and architectures.

Skills

Deep learning research

English communication

Education

PhD in computer science, bioinformatics, or related field

Job description

Postdoctoral research in plant regulatory genomics and artificial intelligence

The Center for Quantitative Genetics and Genomics (QGG) at Aarhus University

You will design new sequence-to-expression deep learning models that predict gene expression from DNA sequence in plants, using new experimental datasets generated in the project. The position includes a 6- to 12-month research stay at Cold Spring Harbor Laboratory (CSHL), USA, combining plant genomics expertise at Aarhus with AI expertise at CSHL.

This is an opportunity to advance the state of the art in AI for plant biology while working across two leading research environments. For more information, feel free to reach out to Guillaume Ramstein (QGG) and Peter Koo (CSHL).

Expected start date and duration of employment

This is a 2-year position from April 1st 2027, or as soon as possible.

Job description

You will advance the field of artificial intelligence applied to regulatory genomics, as part of the GRASP project funded by the Independent Research Fund Denmark. In this project, you will leverage new training sets, build novel deep learning architectures and define dedicated learning objectives, to learn the effects of genetic variants on gene expression.

The position will focus on data science and genomics in a model plant species, Brachypodium distachyon. You will work at the cutting edge of AI in biology and propose new solutions to predict the effects of regulatory variants in plant genomes, which remains an open research problem in plant genomics.

These activities will be carried out in close collaboration with the Koo lab, a leading group in AI and regulatory genomics at Cold Spring Harbor Laboratory (CSHL), USA. As part of this collaboration, the position will include a 6- to 12-month research stay in the Koo lab.

Your profile

Applicants should hold a PhD in computer science, bioinformatics, or a related field, or expect to complete it before the start date. They should have research experience in deep learning.

Applicants are expected to have published in international peer-reviewed journals, preferably on topics related to AI and genomics. Experience in developing new deep learning techniques (model architectures or learning objectives) is especially relevant to this position.

Good communication skills in English are required, as well as the ability to work in an interdisciplinary team of AI experts, computational geneticists, and plant biologists.

Who we are

The Center for Quantitative Genetics and Genomics (QGG) is a major center for research and education in quantitative genetics and genomics at Aarhus University. We conduct basic and applied research in animal, plant, and human genetics. Our focus areas include quantitative genetics, artificial intelligence applied to agriculture and medicine, population genetics, and integrative genomics. Research within QGG is characterized by a very close synergy between method development and application on practical problems across species, in collaboration with industry partners. QGG is an international research center with about 70 employees and visiting researchers from over 15 nations. QGG works in teams and strives for an excellent working environment, in which wevalue self-leadership, open communication, and commitment to diversity and inclusion.

What we offer

The succesful candidate will be offered:

• A 6- to 12-month research stay in the Koo lab at Cold Spring Harbor Laboratory (CSHL), USA, providing international experience and the opportunity to work across two leading labs in plant genomics and AI.
• Computational ressources, including the GenomeDK high-performance computing cluster, with growing capabilities such as high-memory nodes and state-of-the - war GPUs.
• An interdisciplinary interdisciplinary environment, in which the candidate will be able to exchange across research fields (machine learning, bioinformatics, biology, and quantitative genetics) and applications (plant biology, agriculture, and biomedicine).
• A research environment characterized by collaboration, professionalism, commitment to diversity and inclusion, and success in mentoring and supervision.
• A healthy work-life balance.

Place of work and area of employment

The primary place of work is C. F. Møllers Allé 3, 8000, Aarhus (Denmark), and the area of employment is Aarhus University with related departments.

The position will also include a 6- to 12-month research stay at 1 Bungtown Rd, Cold Spring Harbor, NY 11724, United States. The time and duration of the research stay may be negotiated with the supervisors Guillaume Ramstein and Peter Koo.

Contact information

For further information, please contact:

• Tenure-Track Assistant Professor Guillaume Ramstein,[phone], [e-mail]
• Associate Professor Peter Koo, [phone], [e-mail]

Deadline

Applications must be received no later than November 20th, 2026.