Postdoctoral Researcher (f/m/d) in the field of Deep Learning for the cereal Gene Regulation 1. Juli 2026 Bewerbungszeitraum vom 01. Juli 2026 bis 22. Juli 2026 Referenznummer 26/06/26

The group investigates how genetic variation shapes gene regulation, protein function, and, ultimately, observable plant traits. Using deep learning and network analysis, we aim to enhance crop performance through the discovery and annotation of regulatory variants that can guide breeding and gene-editing approaches.

We are seeking a Postdoctoral Researcher to join our team within the BMFTR-funded project Twin – A Digital Discovery Platform for Cereal Genetic Resources, to infer the cereal pan-regulome and its functional variation in wheat and barley.

Your tasks:

Design, train and interpret deep-learning models to infer regulatory sequence features across barley and wheat genomes.

Integrate genome assemblies, WGS variant calls and large-scale RNA-seq data.

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