1. Genetic architecture of photosynthetic traits in barley under dynamic light and temperature conditions (S. Matsubara, FZJ)

Pronounced genetic variations in photosynthesis-related traits have been reported across barley populations under different environmental conditions. Leveraging genetic resources and genomic information in combination with advanced phenotyping platforms, this project aims to identify QTLs and genetic variants underlying high photosynthetic performance and resilience of barley under dynamic light and temperature conditions. The project will be conducted across two institutes, Forschungszentrum Jülich and IPK Gatersleben.

Qualification needed
High mobility (between FZJ and IPK) and experience in GWAS and QTL analysis are essential. Experience in plant phenotyping and transcriptomics is desirable.

2. Gene regulatory networks governing barley shoot development - from genes to growth in 4D (R. Simon, HHU)

The shoot system of monocotyledonous plants such as barley generates a complex set of meristems that develop coordinately and generate branches or floral organs. Spatial and single cell based transcriptomic tools allow us now to investigate RNA patterns in 3D space and over time. We will extend available datasets for barley inflorescence stages to 4D, identify crucial regulators for developmental transitions and test their function in vivo, with the goal to explore the phenotypic space for productive barley architectures.

Qualifications needed
expertise in transcriptomics, gene regulatory networks, plant phenotyping, microscopy, gene editing, bioinformatics. Experience with R is beneficial.

3. Experimental evolution of plant-associated microbial communities (L. Rose, HHU, R. Garrido-Oter, MPIPZ)

Experimental evolution offers a powerful framework to study microbial adaptation. Long-term evolution experiments (LTEEs) in microbial systems have revealed principles of evolutionary repeatability, clonal interference, and convergence. However, most of this work has been restricted to single-species or simplified communities in free-living systems. How evolutionary dynamics unfold in complex, host-associated microbiota remains an open question. The overarching goal of this project is to investigate the evolutionary mechanisms underlying host adaptation and beneficial function in root-associated microbial communities. Using complementary experimental evolution platforms in Arabidopsis and barley, you will (i) identify genetic and ecological determinants of root microbiota adaptation, (ii) evaluate the role of host genotype in shaping evolutionary outcomes, and (iii) engineer evolved microbial communities with improved root colonization capacity plant growth-promoting properties.

Qualifications needed
Microbial isolation and culturing, plant phenotyping, metabarcoding, NGS analysis, Biostatistics

4. The Secret Lives of Soil-Borne Fungal Pathogens: Spatiotemporal Dynamics of Intermicrobial Interactions in Soils (B. Thomma, UoC)

Many fungal plant pathogens have life stages in soil, where they encounter a wealth of competitor microbes. These fungi may deploy antimicrobial effector proteins to manipulate such competitors. This project aims to characterize intermicrobial interactions mediated by antimicrobial effectors in the context of root-associated microbial communities. We will investigate how effector-driven interactions shape microbial community composition across soils and environmental conditions, and how they contribute to host-associated ecosystem adaptation. By linking molecular mechanisms to community-level outcomes, this work will advance our understanding of soil and root microbiome biology and may inform the development of beneficial microbial inoculants that improve plant health and are more robust to pathogen manipulation.

Qualifications needed
Bioinformatics, Spatiotemporal Microbiota Profiling, Microfluidics, Microbial Ecology, Functional Genetics, Fungal Genetics

5. Tissue-Specific Immunometabolic Strategies in barley and Arabidopsis during Biotic Stress (A. Zuccaro, UoC)

Root diseases caused by fungal pathogens are a major threat to cereal production, yet the molecular mechanisms underlying root tissue collapse remain poorly understood. This project explores how root-infecting fungi induce a ferroptosis-like form of regulated cell death in barley by perturbing iron homeostasis, redox balance, and lipid metabolism. By combining fungal genetics, multi-omics approaches, advanced imaging, and cell-type–resolved transcriptomics, we will identify pathogen-derived molecules that trigger lipid peroxidation and define plant metabolic pathways that determine susceptibility or tolerance. The project aims to establish a mechanistic framework for ferroptosis-driven root disease and to reveal molecular entry points for improving cereal root resilience under biotic stress.

Qualifications needed
biochemestry; Fungal genetics / effector biology; Single-cell or single-nucleus transcriptomics; Lipid metabolism / lipid peroxidation or HPC / data analysis pipelines

6. Soil-Inspired Microfluidics for Root–Microbe Dynamics (G. Grossmann, HHU)

Soil ecosystems, including their microscopic microbial niches, play a central role in plant health, ecological resilience, and human nutrition. Achieving a mechanistic understanding of this complexity requires experimental approaches that systematically capture the effects of physical, chemical, and biological heterogeneity. This project will determine how the structured rhizosphere environment shapes root–microbe interactions and colonization, providing a basis for the rational design of beneficial root–microbe partnerships.
To this end, we will develop imaging-compatible, patterned microfluidic devices to enable real-time monitoring of root system colonization in soil-mimicking, spatially structured environments. Using these platforms, we will (i) quantify how diffusional limitations and physical confinement govern microbial movement and establishment on roots, (ii) elucidate how infochemicals and antimicrobials contribute to rhizosphere patterning, and (iii) define how rhizosphere spatial organization modulates functional interactions between roots and individual microbes or complex microbiomes.

Qualifications needed
We seek a postdoctoral researcher with a PhD in bioengineering/biophysics/chemical or biomedical engineering, quantitative microbiology, plant cell biology, or a related field, with demonstrated expertise in live fluorescence microscopy, quantitative image analysis, and microfluidic device design. The successful candidate will independently operate high-resolution/high-sensitivity imaging systems, develop reproducible analysis pipelines (e.g., Python/Fiji/R) to quantify microbial colonization dynamics, and work confidently with bacterial cultures and fluorescent plant reporter lines. A key responsibility is to analyze and/or model flow and mass transport (advection–diffusion) to connect device geometry and microenvironmental conditions to experimentally observed diffusion profiles and interaction outcomes; experience with COMSOL or equivalent modeling frameworks is a strong plus.

7. GRN Foundry – Context-Aware Foundation Models for Plant Gene Regulation (J.J. Szymanski, FZJ, T. Jores, HHU)

This project explores how artificial intelligence and experimental screening can be combined to better understand and engineer gene regulatory sequences controlling key agronomic traits of the CEPLAS consortium with special focus on development in cereal crops. We will develop computational models that learn regulatory patterns from genomic data and link them to high-throughput experimental assays measuring regulatory activity in plant systems. By iteratively connecting AI-based predictions with experimental readouts, the project establishes a feedback loop between modelling and wet-lab screening. This interdisciplinary setup offers a unique opportunity to work at the interface of machine learning, regulatory genomics, and plant synthetic biology within a collaborative research environment.

Qualifications needed

• Deep learning / machine learning (Python / PyTorch or similar ML frameworks)
• Bioinformatics - NGS, genomic sequence analysis
• Molecular biology (wet-lab experience)
• Plant biology (basic understanding)
• Single-cell NGS (desirable)
• Crops genomics (desirable)
• Gene regulation (desirable)

8. Synthetic bioprinted tissues for model-supported predictive analysis (M. Zurbriggen, HHU)

We are seeking a Postdoctoral researcher to pioneer the development of synthetic plant tissue analogues. This project moves beyond traditional observation to reconstruct plant development in vitro, using a synthetic biology approach to decode how Gene Regulatory Networks (GRNs) and signaling drive tissue architecture.

Key Research Pillars:

• 3D Bioprinting: Designing precise 2D/3D architectures using Arabidopsis/barley cells and custom bio-inks.
• Optogenetics: Implementing high-resolution 4D control of cell fate.
• Synthetic Biology: Engineering synthetic GRNs to program cell function.

Goal: To establish a predictive framework for the ab initio design of SMART plants. Synthetic reconstruction of tissues to validate mechanistic models and engineer novel traits for resilient, high-efficiency crops within the CEPLAS III cluster.

Required Qualifications

• Ph.D. in Relevant Field: Molecular Biology, Synthetic Biology, Biotechnology, Bioengineering, or Plant Physiology.
• Advanced Molecular Cloning: Expert proficiency in Golden Gate, Gibson Assembly, and CRISPR/Cas-based genome editing or Prime Editing.
• Plant Cell Systems: Extensive experience working with plant cell cultures, specifically protoplast isolation (Arabidopsis/Barley) and callus induction.
• Microscopy & Imaging: Hands-on experience with confocal laser scanning microscopy and quantitative image analysis (e.g., ImageJ/Fiji, Imaris).

Desired additional techncial expertise:

• Tissue Engineering, Experience with 3D bioprinting
• Computational Literacy: Basic programming (Python/R) for analyzing single-cell RNA sequencing (scRNA-seq) data, AI-basics

Soft Skills & Collaborative Mindset

• Interdisciplinary Communication: Ability to work at the intersection of biology and engineering.
• Project Management: Experience in coordinating collaborative efforts
• Scientific Writing: A track record of publications in high-impact peer-reviewed journals.

9. GRNs governing barley shoot development galore - towards 4D data across many accessions BARVISTAnext (B. Usadel, FZJ)

The project will investigate how gene regulatory networks control shoot and meristem development in barley. The postdoctoral researcher will integrate spatially resolved gene expression data from multiple spatial data sets with genomic and epigenomic information to reconstruct regulatory interactions at cellular resolution. Building on our publicly available BARVISTA platform, the project will expand existing barley expression maps and develop computational methods to identify key regulators underlying developmental transitions. By combining data from multiple barley accessions with predictive models of gene regulation, the project aims to generate mechanistic insights into how genetic variation shapes plant architecture.
Please see e.g. Demesa-Arevalo E et al. (2026) Imputation integrates single-cell and spatial gene expression data to resolve transcriptional networks in barley shoot meristem development. Nature Plants. doi: 10.1038/s41477-025-02176-6.

Qualifications needed

• Background in bioinformatics and/or computational biology
• Hands on experience with spatial transcriptomics and/or single-cell /single-nucleus gene expression data
• Python and/or R knowledge
• Ideally experience in gene regulatory network (GRN) inference
• A strong background in plant biology
• Experience in High-performance computing (HPC) is a plus but not necessary

10. Understanding the structure-function relationship of leaf photosynthesis through multi-scale modelling (N. Töpfer, UoC)

Photosynthesis is a fundamental process of life. Its efficiency is shaped by leaf anatomy, i.e. the spatial organization of cells and vasculature, the underlying biochemical processes, and environmental conditions. Within these physical and biochemical constraints, leaves must balance critical trade-offs, such as minimizing water loss while maximizing carbon assimilation. Understanding how structure and function interact to achieve optimal performance requires a quantitative, mechanistic approach. This project develops a multi-scale model that explicitly represents leaf anatomy, integrates biochemical models of photosynthesis and carbon assimilation, and accounts for environmental factors. By applying this framework across C3, C4, and intermediate photosynthetic types, we will gain fundamental insights into leaf functioning that inform carbon-concentrating mechanism engineering and crop improvement strategies.

Qualifications needed
Strong modelling skills in metabolic modelling (constraint-based / FBA, kinetic modelling), reaction-diffusion modelling, or finite element modelling; a background in physics, mathematics, bioinformatics or related fields and a keen interest in applying computational approaches to understand plant functioning

11. Understanding and engineering carbon allocation strategies and root trait outputs for improved phosphorus acquisition (R. Giehl, IPK)

Improving nutrient use efficiency represents a sustainable approach to reduce fertilizer inputs and mitigate eutrophication of ecosystems. This project aims to decode and engineer plant carbon allocation strategies to enhance phosphorus acquisition through improved plant-autonomous decisions. This will be achieved by generating and testing the first generation of SMART plant prototypes, in which engineered or synthetic promoters trigger predefined and condition-dependent modifications in carbon-demanding root morphological and metabolic traits. With the generated plants, we will evaluate the effectiveness and metabolic costs of engineered root responses for efficient phosphorus capture while investigating trade-offs and synergisms resulting from the modulation of single and multiple root traits.

Qualifications needed
Demonstrated scientific publication record.
Experience with: advanced cloning, Arabidopsis cultivation and phenotyping, confocal microscopy.
Of advantage: experience with root exudate analysis and/or bacterial cultivation.

12. Developing trans-generationally stable centromere elimination (K. Schneeberger, MPIPZ/HHU)

Centromeres are essential chromosome regions that control inheritance, yet they remain among the least understood parts of plant genomes. Recent advances now allow their complete, error-free reconstruction and functional analysis. This project pioneers new strategies to precisely annotate, target and selectively eliminate plant centromeres using CRISPR-based genome engineering. By defining functional centromere elements and developing methods for their controlled removal, we aim to enable chromosome-scale engineering, non-Mendelian inheritance and the creation of stable plant artificial chromosomes. These technologies will establish powerful new foundations for modular trait stacking and next-generation plant breeding.

Qualifications needed
Experience in plant genomics and the analysis of centromeres