11.04.2024

Postdoctoral researcher (f/m/d)

Leibniz Centre for Agricultural Landscape Research (ZALF), Müncheberg

The mission of the Leibniz Centre for Agricultural Landscape Research (ZALF) as a nationally and internationally active research institute is to deliver solutions for an ecologically, economically and socially sustainable agriculture – together with society. ZALF is a member of the Leibniz Association and is located in Müncheberg (approx. 35 minutes by regional train from Berlin-Lichtenberg). The institute also maintains locations in Dedelow and Paulinenaue.

The Research Platform Data Analysis & Simulation is offering a 3.5-year postdoc position as part of FAIRagro. FAIRagro is a consortium in the National Research Data Infrastructure (NFDI) in Germany. Aims and tasks of FAIRagro comprise the development of a networked research data management (RDM) for agrosystems research and the establishment of an interoperable, scalable, quality-assured and user-friendly research data infrastructure under consideration of the FAIR data principles. This position will support the development of RDM solutions for agroecosystem research from field to landscape and larger scales.

We are offering a full-time position starting from August 2024 until end of February 2028 at our location in Müncheberg as:

Postdoctoral researcher (f/m/d)

Your tasks:

  • improve an existing metadata model and scheme for complex agricultural experimental and monitoring data
  • establish data quality, plausibility services and a data-fitness-for-use tool for agricultural datasets based on merging advanced statistics, machine learning and biophysical modelling
  • regular interaction with the FAIRagro team to develop appropriate infrastructure
  • publication of results in peer-reviewed scientific journals

Your qualifications:

  • PhD in agronomy, environmental sciences, biology, geography, or data science
  • experience in agricultural or environmental research
  • basic knowledge of or willingness to familiarise with advanced statistical methods, machine learning approaches and Bayesian Models
  • basic knowledge of or willingness to familiarise with biophysical crop yield models
  • basic scripting skills (e.g., R, Python, …)
  • experience working with FAIR research data management, Open Software and Open Science would be beneficial
  • good team work skills with interest to collaborate across disciplines
  • as an internationally research institution, located in Germany we require good to very good written and spoken English skills and the willingness to take part in further training as part of the language courses in German offered internally

We offer:

  • interdisciplinary working environment that encourages independence
  • opportunity to collaborate with leading international scientists and networks in cropping and eco-system analysis and research data management
  • strong institutional commitment to a good work-life balance
  • classification according to the collective agreement of the federal states (TV-L) up to EG13 with up to 100% weekly working time (including special annual payment), though part time working arrangements are possible
  • company ticket
  • in-house language courses in German and English

Women are particularly encouraged to apply. Applications from severely disabled persons with equal qualifications are favored. Please send your application preferably online.

If you have any questions, please do not hesitate to contact Prof. Dr.Gunnar Lischeid, lischeid(at)zalf.de.

For cost reasons, if any application documents or extensive publications are sent by post, they can only be returned if an adequately stamped envelope is attached.

If you apply, we collect and process your personal data in accordance with Articles 5 and 6 of the EU GDPR only for the processing of your application and for purposes that result from possible future employment with the ZALF. Your data will be deleted after six months.