Postdoctoral position in crop modelling in climate adaptation and resilience

**Job Description**
This postdoctoral position at the Department of Agroecology, Aarhus University, focuses on advancing crop modelling for climate adaptation and resilience. The role involves developing precise solutions for climate resilience in agriculture across the EU Boreal region, specifically by designing adaptation strategies using crop modelling and collaborating with local actors to address climate risks. A primary responsibility will be to develop an interdisciplinary modelling platform to evaluate adaptation strategies under future climate and crop systems at larger spatial units, leveraging established field experiments and full-scale facilities in Denmark and the boreal region of Europe. The successful candidate will analyze data from field to spatial scale and investigate spatial optimization approaches to enhance model parameterization.

**Skills & Abilities**
• Collaborative skills and ability to demonstrate commitment in teams
• Fondness of taking the initiative and the motivation to pursue a scientific career
• Documented experience in scientific writing and publication in peer-reviewed scientific journals
• Research experience in process-based crop modeling, uncertainty characterization, digital agronomy, or remote sensing
• Teaching and supervision experience at the BSc and MSc level (preferred)
• Interest and experience in developing competitive national and international research applications (preferred)
• Experience in programming languages (e.g., Python/R) and analytical skills in model evaluation (preferred)
• Experience in advanced statistical analysis of results (preferred)
• Experience with crop model calibration and evaluation (e.g., DSSAT, APSIM, or equivalent) (preferred)
• Insight into analyzing data-intensive measurements and sensitive analysis (preferred)

**Qualifications**
Required Degree(s) in:
• Agricultural science
• Crop modeling
• Agroecology
• Digital agronomy
• Similar fields

**Experience**
Experience Required:
• Documented experience in scientific writing and publication in peer-reviewed scientific journals
• Research experience in some of the areas of process-based crop modeling, uncertainty characterization, digital agronomy, remote sensing
Other:
• Teaching and supervision experience at the BSc and MSc level (preferred)
• Interest and experience in developing competitive national and international research applications (preferred)
• Experience in programming languages (e.g., Python/R) and analytical skills in model evaluation (preferred)
• Experience in advanced statistical analysis of results (preferred)
• Experience with crop model calibration and evaluation, such as DSSAT, APSIM, or equivalent (preferred)
• Insight into analyzing data-intensive measurements and sensitive analysis (preferred)

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