Website Leibniz Institute of Plant Genetics and Crop Plant Research (IPK)
The Network Analysis and Modelling group investigates how genetic variation shapes gene regulation, protein function, and, ultimately, observable plant traits. Using machine learning and network analysis, we aim to enhance crop performance through the discovery and annotation of gene variants that can guide breeding and gene-editing approaches.
We are seeking a Postdoctoral Researcher to join our team to work on machine learning-supported rapeseed genomics and breeding.
Your tasks:
- You design, train and interpret deep-learning models to predict regulatory gene variants in rapeseed genomes.
- You integrate large-scale sequence and RNA-seq data from internal and public resources.
- You build a reference library of predictive regulatory motifs.
- You use network analysis and random-forest approaches to identify transcription-factor master regulators and derive targets for gene editing / TILLING.
- You integrate multi-omics data to identify genotype-phenotype associations.
- You ensure FAIR data management, collaborate closely with geneticists, breeders and industry partners and publish your results in high-impact journals.
- You supervise MSc/PhD students and contribute to new grant proposals.
Your application:
More details you find here and how to apply
We are looking forward to receiving your online-application until 25.07.2025.
To apply for this job please visit www.ipk-gatersleben.de.