Postdoctoral research in plant regulatory genomics and artificial intelligence

Postdoctoral Research In Plant Regulatory Genomics And Artificial Intelligence

The Center for Quantitative Genetics and Genomics (QGG) at Aarhus University, Denmark, invites applications for a two-year postdoctoral position in plant regulatory genomics and artificial intelligence, starting 1 April 2027.

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.

What we offer: The successful 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 resources, including the GenomeDK high-performance computing cluster, with growing capabilities such as high-memory nodes and state-of-the-art GPUs.
• An 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, +45 42 52 12 66, [email protected]
  • Associate Professor Peter Koo, +1 516 367 5520, [email protected]

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