PhD Position on Predictive Plant–Microbiome–Pathogen Interactions

Sport Society; Utrecht; On-site; EUR 38,000 - 48,000; Full time

Benefits offered by this job

Pension scheme

Partially paid parental leave

Flexible terms of employment

Job summary

Utrecht University in the Netherlands invites applications for a PhD position in Predictive Plant–Microbiome–Pathogen Interactions. You will join the Plant-Microbe Interactions group within the NWO Vici project ResistoBiome, exploring how potato microbiomes influence disease outcomes.

You will perform high-throughput phenotyping, microbiome profiling, predictive modelling, and validation experiments, collaborating across microbiology, plant pathology and bioinformatics teams to advance resilient

Qualifications

• The candidate holds an MSc in plant biology, microbiology, molecular biology or related discipline.
• Experience with experimental laboratory work or plant experiments.
• Interest in plant–microbe interactions and microbiome research.
• Proficiency in quantitative biology, phenotyping and data analysis.
• Ability to communicate research findings and collaborate across disciplines.

Responsibilities

• Perform large-scale potato experiments using diverse soil microbiomes.
• Use automated phenotyping to quantify growth, physiology and disease.
• Profile root and leaf microbiomes via amplicon sequencing.
• Analyze integrated microbiome and phenotyping data.
• Contribute to machine-learning models predicting pathogen invasion.
• Identify microbes associated with disease outcomes and test them experimentally.
• Collaborate with microbiology, plant pathology, bioinformatics and modelling teams.

Skills

MSc degree

Plant biology

Lab experiments

Data analysis

English proficiency

Education

MSc degree in related field

Tools

R

Python

Phenotyping tools

Job description

PhD Position on Predictive Plant–Microbiome–Pathogen Interactions

How does the microbiome surrounding a plant determine whether a pathogen can successfully invade? And can we predict disease outcomes from microbiome composition and plant phenotypes? Join us as a PhD candidate to investigate how the potato microbiome influences interactions with two major plant pathogens: Phytophthora infestans and Ralstonia solanacearum. You will combine high-throughput plant phenotyping, microbiome profiling, predictive modelling and targeted experimental validation to identify the microbial factors that make plants more resilient to disease.

You will join the Plant-Microbe Interactions group and work within the NWO Vici project ResistoBiome: Predictive microbiome modelling for resilient and sustainable potato cropping systems.

In this project, you will investigate why the same pathogen can cause severe disease in one microbial environment but establish poorly in another. You will work with a unique collection of 100 Dutch agricultural soil microbiomes and grow potato plants in the automated phenotyping facilities of the Netherlands Plant Eco-phenotyping Centre (NPEC)

How does the microbiome surrounding a plant determine whether a pathogen can successfully invade? And can we predict disease outcomes from microbiome composition and plant phenotypes? Join us as a PhD candidate to investigate how the potato microbiome influences interactions with two major plant pathogens: Phytophthora infestans and Ralstonia solanacearum. You will combine high-throughput plant phenotyping, microbiome profiling, predictive modelling and targeted experimental validation to identify the microbial factors that make plants more resilient to disease.

Your job

You will join the Plant-Microbe Interactions group and work within the NWO Vici project ResistoBiome: Predictive microbiome modelling for resilient and sustainable potato cropping systems.

In this project, you will investigate why the same pathogen can cause severe disease in one microbial environment but establish poorly in another. You will work with a unique collection of 100 Dutch agricultural soil microbiomes and grow potato plants in the automated phenotyping facilities of the Netherlands Plant Eco-phenotyping Centre (NPEC)

Using high-resolution imaging, you will follow plant growth, physiology and disease development after infection with Phytophthora or Ralstonia.

You will combine these phenotyping data with bacterial and fungal microbiome profiles to build predictive models of pathogen invasion and plant performance. Working in close collaboration with with a postdoctoral researcher and a fellow PhD candidate, you will identify microbial taxa and microbial interactions that are most strongly associated with disease resistance or susceptibility.

A key part of your project will be to move from prediction to biological understanding. You will select promising microbes emerging from the models, isolate and experimentally test them, and investigate how they influence pathogen establishment and plant health. This will allow you to ask not only which microbes predict disease outcomes, but also why they matter.

During your PhD, you will:

• perform large-scale potato experiments using 100 contrasting soil microbiomes;
• use automated high-throughput phenotyping to quantify plant growth, physiology and disease development;
• profile root and leaf microbiomes using amplicon sequencing;
• analyse integrated microbiome and phenotyping datasets;
• contribute to machine-learning models predicting pathogen invasion success and plant resilience;
• identify microbial taxa and interactions associated with contrasting disease outcomes;
• isolate and experimentally validate selected candidate microbes;
• design follow-up experiments to understand how protective microbes influence plant–pathogen interactions;
• collaborate closely with researchers in microbiology, plant pathology, phenotyping, bioinformatics and predictive modelling.

The project gives you the opportunity to work across scales: from thousands of plants and complex microbiome datasets to mechanistic experiments with individual microbial isolates.

Your qualities

You enjoy combining experimental biology with quantitative approaches and are eager to develop skills in microbiome data analysis and predictive modelling;

You have:

• an MSc degree in plant biology, microbiology, molecular biology, plant pathology, biotechnology, bioinformatics or a related discipline;
• experience with experimental laboratory work or plant experiments;
• a strong interest in plant–microbe interactions and microbiome research;
• an interest in quantitative biology, phenotyping and data analysis;
• the ability to organise research activities effectively, to communicate research findings to different audiences and collaborate across disciplines;
• proficiency in spoken and written English.

Experience with plant pathogens, microbiome sequencing, image-based phenotyping, R/Python, statistics or machine learning is an advantage. We do not expect candidates to already have expertise in all of these areas.

Our offer

• a position for 18 months, with an extension to a total of four years upon a positive assessment in the first 18 months;
• a gross monthly salary starting at € 3,204 in the first year and increasing annually up to €4,051 in the fourth year, based on full-time employment (salary scale P under the Collective Labour Agreement for Dutch Universities (CAO NU));
• 8% holiday pay and 8.3% year-end bonus;
• a pension scheme, partially paid parental leave and flexible terms of employment based on the CAO NU.

In addition to the terms of employment laid down in the CAO NU, Utrecht University also offers a range of its own schemes for employees. This includes arrangements for professional development , various types of leave, and options for sports and cultural activities . You can also tailor your employment conditions through our Terms of Employment Options Model. In this way, we encourage you to keep investing in your personal and professional development. For more information, please visit Working at Utrecht University .

About us

A better future for everyone. This ambition motivates our scientists in executing their leading research and inspiring teaching. AtUtrecht University , the various disciplines collaborate intensively towards majorstrategic themes . Our focus is on Dynamics of Youth, Institutions for Open Societies, Life Sciences and Pathways to Sustainability.Sharing science, shaping tomorrow .

Working at the Faculty of Science

The Faculty has six departments: Biology, Pharmaceutical Sciences, Information & Computing Sciences, Physics, Chemistry and Mathematics. Together, we work on excellent research and inspiring education. We do so, driven by curiosity and supported by outstanding infrastructure. Visit us on LinkedIn and discover how you can become part of our community.

You will be embedded in theDepartment of Biology within thePlant-Microbe Interactions group where you will be part of the research team ofDr. Roeland Berendsen.

More information

For more information, please contactDr. Roeland Berendsen [e-mail] .

Candidates for this vacancy will be recruited by Utrecht University.

Knowledge security screening can be part of the selection procedures of academic staff. We do this, among other things, to prevent the unwanted transfer of sensitive knowledge and technology.

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The application deadline is 2 October 2026.