Spatial evaluation of Precision Agriculture Strategies for Optimizing Nitrogen Fertilization and Reducing Greenhouse Gas Emis...
Title
Spatial evaluation of Precision Agriculture Strategies for Optimizing Nitrogen Fertilization and Reducing Greenhouse Gas Emissions
Research area and project description
Climate change is intensifying the challenges of modern agriculture. From unpredictable weather conditions to increased nutrient losses which threaten both crop productivity and environmental sustainability. Technical advancements, UAV applications, big data analytics, and AI tools are being increasingly used in agriculture as promising tools to help tackle these challenges. However, there is still a significant gap in knowledge and quantifiable effects on how those solutions effectively reduce environmental impacts in space and time in full fields.
The objective of this research program is to quantify the environmental and agronomic benefits of using precision agriculture, for example looking at crop yield, nutrient leaching, emissions and input efficiency. This will be achieved by combining above-ground observations using remote and proximal sensing and field measurements with below-ground data including root measurements, soil spatial characterization, and nutrient leaching assessment.
The goal is to test how the use of both system-based modelling and machine learning can help to perform a spatial-temporal validation that integrates high-resolution spatial and temporal variability that can serve as a framework for smart decision-making in agriculture
Project description
For technical reasons, you must upload a project description. Please simply copy the project description above and upload it as a PDF in the application.
Qualifications and specific competences
Applicants to the PhD position must have a master’s degree in agronomy, precision agriculture.
Experience in working in Digital and/or Precision agriculture would be advantageous. Handling remote and proximal sensing data is important, as well as good understanding of data management and modelling.
Place of employment and place of work
The place of employment is Aarhus University, and the place of work is AU-Viborg, Blichers Alle’ 20, Tjele, 8830, Denmark.
Contacts
Applicants seeking further information regarding the PhD position are invited to contact:
- Davide Cammarano, davide.cammarano@agro.au.dk (main supervisor)
- Sheng Wang, swan@agro.au.dk (co-supervisor)
For information about application requirements and mandatory attachments, please see our application guide. If answers cannot be found there, please contact:
How to apply
Please follow this link to submit your application.
Application deadline is 20 May 2025 at 23:59 CEST
Preferred starting date is 01 September 2025
Please note:
- Only documents received prior to the application deadline will be evaluated. Thus, documents sent after deadline will not be taken into account.
- The programme committee may request further information or invite the applicant to attend an interview.
- Shortlisting will be used, which means that the evaluation committee only will evaluate the most relevant applications.
Aarhus University’s ambition is to be an attractive and inspiring workplace for all and to foster a culture in which each individual has opportunities to thrive, achieve and develop. We view equality and diversity as assets, and we welcome all applicants. All interested candidates are encouraged to apply, regardless of their personal background. Salary and terms of employment are in accordance with applicable collective agreement.
Please note in your application that you found the job at Jobindex
