Postdoctoral Researcher in comparative genomics and machine learning for plant biology

Postdoctoral Researcher in Comparative Genomics and Machine Learning for Plant Biology

The EvOmics group at Aarhus University is seeking a postdoctoral researcher to join an interdisciplinary project that combines plant genomics, artificial intelligence, and evolutionary biology. The position is based at the Center for Quantitative Genetics and Genomics (QGG) under the supervision of Asst. Prof. Irene Julca. The position is offered as a two-year appointment, with the possibility of extension, and is available from 1 March 2027 or as soon as possible thereafter.

Climate change is increasing the need to develop crops that can withstand drought, heat, salinity, and other environmental stresses. However, identifying the genes underlying these complex traits remains challenging. This project will combine plant genomics, artificial intelligence, and evolutionary biology to integrate multi-omics and functional information across plants and identify genes associated with stress resilience.

The position is part of the Novo Nordisk Foundation Emerging Investigator grant project “Driving innovation in crop resilience through Comparative QTLomics.” The selected candidate will contribute to five main objectives:

• Apply large language models (LLMs) to collect, extract, and standardise functional information
• Develop computational tools that integrate evolutionary and functional information using comparative genomics and deep learning approaches
• Apply these methods across different crops to identify conserved patterns of stress resilience
• Identify candidate genes associated with key agronomic traits related to resilience
• Contribute to software and web development

  Qualifications include a PhD degree in Bioinformatics, Computational Biology, Computer Science, Mathematics, Physics, or a related field, strong experience with programming in Python, R, or similar languages, background in machine learning or deep learning methods, including Graph Neural Network (GNN), experience with Large Language Models (LLMs) applied to biological data collection, extraction, and standardization, knowledge of multi-omics integration and plant biology is an advantage, familiarity with large biological datasets and high-performance computing is desirable, ability to work independently and collaboratively in an interdisciplinary research environment, and proficiency in written and spoken English.

  The Center for Quantitative Genetics and Genomics (QGG) is an innovative and interdisciplinary center for research and education in quantitative genetics and quantitative genomics. QGG is an international organisation with 70 employees and visiting researchers from more than 20 countries. We perform basic and applied research within plant, livestock, and human quantitative genetics. Our focus areas include quantitative genetics, artificial intelligence applied to agriculture and precision medicine, population genetics, and integrative genomics. QGG is located at the central campus in Aarhus and at the AU Flakkebjerg campus in newly renovated offices with well-developed research infrastructure, laboratories, equipment, and high-performing computing clusters.

  We offer a welcoming and collaborative environment emphasizing teamwork, professionalism, equality, and work-life balance, mentoring for career development, access to high-performance computational resources (with GPUs), a collaborative environment across research fields, including plant biology, quantitative genetics, and population genetics, opportunities for collaboration and research visits with project partners, and participation in international conferences and workshops.

  Applications must be received no later than 12 October 2026. Your application must include the following: Curriculum Vitae, Diploma, Motivation letter, Two recommendation letters.