An der Georg-August-Universität Göttingen Stiftung Öffentlichen Rechts – DNPW - Abt. Graslandwissenschaft ist ab dem 01.04.2026 eine Stelle alsPhD position (65%) (all genders welcome)- Entgeltgruppe 13 TV-L - in Teilzeit mit 65% der regelmäßigen wöchentlichen Arbeitszeit zu besetzen. Die Stelle ist befristet bis 31.03.2030.Topic
“Effect of multiple stress by genotype interactions on resource use efficiency, primary production and stress responses of maize”

This position is open to all qualified individuals (m/f/d) who are eager to engage in cutting-edge, interdisciplinary research at the interface of crop modelling, multiple abiotic-biotic stress interactions, ecological dynamics, and model integration and evaluation, contributing to the DFG-funded Research Unit “Concurrent multiple abiotic and biotic stress interactions in maize: impacts and mechanisms” (MultiStress RU 6101), pending final approval on 11 December 2025.

Project context: The DFG-funded MultiStress RU investigates how maize responds to multiple, interacting abiotic (e.g., drought, nitrogen deficit) and biotic (e.g., Setosphaeria turcica) stress factors. Through an integrated experimental–modelling approach, the project aims to improve our understanding and prediction of crop performance under complex stress environments.

This PhD position will focus on detailed phenotyping, including stress response-related traits as assessed in systematic studies conducted in the field and greenhouse, to investigate aboveground carbon (C) and dry matter partitioning and nutrient use efficiency including defence traits affecting aboveground biomass quality. The PhD position will engage closely with another position studying the belowground biomass allocation. The aim is to analyse the effects of Setosphaeria turcica or Ostrinia nubilalis stress on maize growth, yield, and quality, and its interactions with water and nutrient stress across temperate and tropical environments. It will also help integrating data for novel model routines (e.g. on interactions of stemborer with nitrogen and water deficits).

Main Tasks

Jointly work on data collection of above- and belowground biomass traits in field trials and the greenhouse including

non-destructive (e.g. SPAD, LAI, stomatal conductance) and
destructive (biomass) data


Sample processing via organ-specific separation and subsequent sample processing and lab analyses for nutrient uptake and nutritive value
Analyse data statistically to explore how biotic and abiotic stresses jointly affect yield and quality and resource use efficiency under varying environmental conditions
Collaborate closely with other subprojects within the Research Unit, linking experimental, modelling, and synthesis activities.
Publishing your research in international peer-reviewed journals, presenting research on conferences and actively engage in project-related workshops

Required Qualifications:

Master’s degree (or equivalent) in Crop Science, Agronomy, Agricultural or Environmental Sciences, Plant Pathology, Systems Biology, or a related field
Strong interest in quantitative forage crop production and the interaction between plant physiology, environment, and disease
Proven expertise in field sampling plants above- and belowground
Proven experience in conducting greenhouse trials
Strong laboratory analytical skills of plant biomass (forage value, isotopes, nutrients) including elemental analysis, NIRS, photometry, ICP
Knowledge of maize morphology and its separation
Extensive experience in soil sampling and further processing
Extensive experience in measuring non-destructive plant traits
Solid skills in programming and data analysis (e.g., R, Python)
Experience with Microsoft office tools
Ability to work independently and collaboratively in an interdisciplinary and international team.
Very good command of English, both written and spoken.


We offer:

A dynamic, interdisciplinary, and internationally leading and pioneering research environment within the DFG Research Unit MultiStress, which consists of research consortium of ten universities /research organisations from Germany, Kenya, Italy (+ CIMMYT), representing all important disciplines of crop science.
Excellent supervision and training opportunities in field trial execution, data interpretation, and scientific communication.
Access to unique multi-stress experimental datasets (and travel to associated experimental sites in Germany and Kenya)
Access to high-performance computing infrastructure.
Opportunities for unique international collaboration around maize and participation in versatile project thematic workshops and international conferences.
a four-year PhD position (65% TV-L E13)

For further information, please contact:
PD Dr. Martin Komainda, Grassland Science, University of Goettingen, Germany, E-mail: martin.komainda@uni-goettingen.de or Prof. Dr. Johannes Isselstein, Grassland Science, University of Goettingen, Germany, Email: jissels@gwdg.de
Die Universität Göttingen strebt in den Bereichen, in denen Frauen unterrepräsentiert sind, eine Erhöhung des Frauenanteils an und fordert daher qualifizierte Frauen nachdrücklich zur Bewerbung auf. Sie versteht sich zudem als familienfreundliche Hochschule und fördert die Vereinbarkeit von Wissenschaft/Beruf und Familie. Der beruflichen Teilhabe von schwerbehinderten Beschäftigten sieht sich die Universität in besondere Weise verpflichtet und begrüßt deshalb Bewerbungen schwerbehinderter Menschen. Bei gleicher Qualifikation erhalten Bewerbungen von Menschen mit Schwerbehinderung den Vorzug. Eine Behinderung bzw. Gleichstellung ist zur Wahrung der Interessen bereits in die Bewerbung aufzunehmen.

Bitte reichen Sie Ihre aussagekräftige Bewerbung mit allen wichtigen Unterlagen bis zum 25.01.2026 ausschließlich über das Bewerbungsportal http://obp.uni-goettingen.de/de-de/OBF/Index/76198 ein.

Auskunft erteilt Herr Martin Komainda, E-Mail: martin.komainda@uni-goettingen.de, Tel. 0049551-3924388Hinweis: Wir weisen darauf hin, dass die Einreichung der Bewerbung eine datenschutzrechtliche Einwilligung in die Verarbeitung Ihrer Bewerbungsdaten durch uns darstellt. Näheres zur Rechtsgrundlage und Datenverwendung finden Sie im Hinweisblatt zur Datenschutzgrundverordnung (DSGVO)