Postdoc in Computational Genomics, Pangenomics and LLM-Based Plant Genome Analysis Aarhus University in Denmark

Research theme: This PhD project focuses on predicting gene expression in plants by combining genomic language models with machine learning on gene regulatory networks. The thesis is part of the BioLLM-CRE project and is hosted in the DIADE research unit (Diversity, Adaptation and Development of tropical plants), a joint unit involving IRD, CIRAD and the University of Montpellier . The unit works on plant biodiversity, adaptation mechanisms and plant-environment interactions, using approaches th...

Postdoctoral opportunity in plant regulatory genomics and artificial intelligence at Aarhus University , with collaboration with Cold Spring Harbor Laboratory . The project sits at the intersection of functional genomics , plant quantitative genetics , regulatory genomics , transcriptomics , machine learning , deep learning , and explainable AI . The successful candidate will work with Guillaume Ramstein’s group at the Center for Quantitative Genetics and Genomics (Aarhus University) and Peter K...

Postdoctoral position in plant regulatory genomics and artificial intelligence at Aarhus University (Center for Quantitative Genetics and Genomics, QGG), Denmark. The project is part of the GRASP initiative funded by the Independent Research Fund Denmark . The successful candidate will design new sequence-to-expression deep learning models to predict gene expression from DNA sequence in plants, using new experimental datasets generated in the project. The research focuses on regulatory variants ...

Postdoctoral Researcher in comparative genomics and machine learning for plant biology at Aarhus University , Center for Quantitative Genetics and Genomics. This postdoctoral opening sits in a research project on crop resilience , combining plant genomics , bioinformatics , comparative genomics , multi-omics , evolutionary biology , and machine learning . The project aims to identify genes and conserved patterns associated with stress resilience in crops under challenges such as drought, heat, s...

This postdoctoral project focuses on genome-informed microbial biogeochemical modeling to improve understanding of soil carbon cycling under global warming. The successful candidate will work on quantifying microbial traits from metagenomes and using these traits to develop a microbial-explicit version of the dynamic vegetation model LPJ-GUESS . The post is hosted by the Department of Biology, Faculty of SCIENCE, University of Copenhagen , and is embedded in the Center of Excellence VOLT (Center...