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46230Open Positions

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Internship - Organizing Phenotypic Data for Soil-Plant Model Calibration

Forschungszentrum Jülich
Found 1 month ago
Location
Remote, Germany
Duration (Months)
3 Months
Time
Not disclosed
Work Mode
Remote
Salary
Reasonable remuneration
Visa Help
Not disclosed
Last Verified
1 month ago

Education

  • Bachelor

Skills & Qualifications

Technical Skills

  • Excel skills

Soft Skills

  • organized
  • reliable
  • proactive
  • good communicator
  • enjoy teamwork

Job Description

The CROP (Combining ROot contrasted Phenotypes for more resilient agro-ecosystem) project aims to estimate the beneficial impact of combining contrasting wheat root phenotypes in the same field. We aim to assess the benefits of the combination on water, carbon and nitrogen fluxes and cycles, microbial activity and yield. During the first stage of the project, experiments were carried out in field and laboratory conditions and a soil-plant model was set up. The experimental data can now be used to calibrate and test the model. We are looking for a motivated intern to work on the treatment and storage of the experimental data for usage in the calibration of a plant-soil model. The intern will be in contact with both the modelling and experimental cluster of the project to gain an overview of the experimental setups, as well as of the model parameters. They will also have the opportunity to participate in ongoing field sampling campaigns or laboratory work.

Requirements

  • enrolled as a student at a university
  • strong Excel skills
  • organized, reliable, and proactive
  • good communicator and enjoy teamwork
  • comfortable working in English (at least B2 level according to the CEFR: https://go.fzj.de/languagerequirements )
  • Optional: background in agriculture, environmental or geosciences, and some understanding of soil/plant systems
  • Optional: interest in data science or modelling

Related Field

  • Biology and Biotech

Related Subfield

  • Biology Lab & Research

Languages

  • English

Nice to Haves

  • background in agriculture, environmental or geosciences
  • understanding of soil/plant systems
  • interest in data science or modelling
▶Apply Now

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