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Research Assistant - Forest Ecology​/Wi

in 17489, Greifswald, Mecklenburg-Vorpommern, Deutschland
Unternehmen: Ernst-Moritz-Arndt-Universität Greifswald
Teilzeit position
Verfasst am 2026-09-24
Berufliche Spezialisierung:
  • Forschung/Entwicklung
    Forschungswissenschaftler, Biologie, Biotechnologie
  • Wissenschaft
    Forschungswissenschaftler, Biologie, Umweltwissenschaft, Biotechnologie
Gehalts-/Lohnspanne oder Branchenbenchmark: 32000 - 42000 EUR pro Jahr EUR 32000.00 42000.00 YEAR
Stellenbeschreibung
Stellenbezeichnung: Research Assistant - Forest Ecology 26/Wi15
Location: Greifswald

At the Institute of Botany and Landscape Ecology’s Experimental Plant Ecology Group, which belongs to the University of Greifswald’s Faculty of Mathematics and Natural Sciences, there is a job vacancy,subject to budgetary regulations,that will be available from 1 January 2027 on a fixed-term contract
until 31 March
2030

, for a part-time position (65 %) as

Research Assistant Forest Ecology.

Payment will be made in accordance with pay group 13 TV-L Wissenschaft.

The research group Experimental Plant Ecology at the University of Greifswald’s Institute of Botany and Landscape Ecology conducts research on various topics in forest ecology and peatland research. We combine basic science with practical applications and real-world relevance. One area of focus is the study of processes within the plant root zone, which we investigate using state-of-the-art techniques. Between one-third and more than three-quarters of plant biomass is produced underground.

Roots are crucial for water and nutrient uptake and thus for plant growth, particularly in the context of climate change with its increasingly frequent and severe dry spells. Despite this autoecological and ecosytemic importance, little is yet known about the dynamics of root growth. It is clear, however, that root growth does not correlate directly with above-ground growth dynamics.

In the Experimental Plant Ecology Research Group, we use various methods to quantify and understand root growth. These include ingrowth cores, litterbags, marker horizons and, in particular, minirhizotrons. These are plexiglass tubes installed in the rhizosphere which, with the aid of a scanner, enable the observation of root development. The method has been significantly refined in our group’s previous projects. Thanks to the scanner’s automation, image data can now be transferred at the desired temporal resolution directly from the field to databases, and the scans are analysed automatically using an AI algorithm (‘Root Detector’).

These tools now provide completely new insights into the spatiotemporal dynamics of root growth.

The position advertised here involves applying and further developing these methods in the field and in controlled experiments. Technical support is available.

Long-term observation series have already been established at field sites in beech forests in north-eastern Germany and north-western Poland, where above-ground growth (dendrometers), phenology (phenocams) and root growth (manual mini-rhizotron scans) have been recorded. These measurement series are to be continued and expanded to include automatic root scanners, and then analysed with regard to the interplay between above- and below-ground growth dynamics.

Controlled experiments in mesocosms or individual pots are also possible and encouraged. For example, the position holder could use these methods to investigate the significance of the establishment phase of forest trees for their subsequent root architecture and, thus, also their later adaptability to drought.

Developing your own research focus and profile is definitely encouraged!

Tasks:

  • Data collection at field sites and its analysis
  • Planning, conducting and analysing controlled experiments
  • Publication of the results in scientific journals
  • The aim is to complete a cumulative PhD on the topic

Requirements:

  • A master’s degree (or equivalent) in Biology, Ecology, Geoecology, or a related discipline by the time employment starts
  • A solid knowledge base in plant ecology; knowledge of forest ecology and root growth is an advantage
  • Experience with and enthusiasm for statistical analysis of research data, preferably in R
  • High level of motivation to work in an interdisciplinary and international research and training environment
  • Ability to work…
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