Applicants are invited for a PhD fellowship/scholarship at Graduate School of Technical Sciences, Aarhus University, Denmark, within the Agroecology programme. The position is available from 1 November 2026 or later. You can submit your application via the link under 'how to apply'.
 

Title:
Remote Sensing for Climate-smart Agriculture

Research area and project description:
Department of Agroecology at Aarhus University, Denmark, is offering a PhD position in remote sensing for climate-smart agriculture, starting 01 October 2026 or earliest possible thereafter. The position is available for a 3-year period.

Food security, climate change and loss of biodiversity represent three of today’s major environmental sustainability challenges. Finding solutions to these challenges requires studies that extend across multiple spatial and temporal scales. The Pioneer Center Land-CRAFT was established in June 2022 to undertake fundamental and applied research that addresses these issues. The center brings together experts on climate impact research and process-based modelling of biogeochemistry, agronomy, biology and geography from Aarhus University and University of Copenhagen, as well as international partners. Field experiments, digital technologies -- including modelling and remote sensing, as well as interactions with stakeholders are key components of Land-CRAFT.

Climate-smart agriculture aims to provide innovative solutions to improve crop production, reduce greenhouse gas emissions, and strengthen agroecosystem resilience to climate extremes. Timely, high-resolution information on agroecosystem dynamics is critical for unlocking the complex interactions among crops, management activities, and environmental factors. This project aims to develop novel remote sensing algorithms and knowledge-guided machine learning framework to monitor crop nitrogen, agroecosystem productivity and greenhouse gas fluxes for climate-smart agriculture. The remote sensing derived information will be used to inform climate-smart agriculture practices and policies for the Danish and EU wheat cropping systems. In this project, the PhD student will work on the following tasks. 

(1) To develop novel remote sensing algorithms to integrate soil-vegetation radiative transfer models and deep learning into knowledge-guided machine learning to quantify crop productivity, nitrogen status, and yield from satellite remote sensing at the regional or global scale. The candidate will leverage a diverse suite of remote sensing modalities (hyperspectral, solar-induced fluorescence, multispectral, thermal infrared, passive and active microwave) across multiple scales. 

(2) To assess the potential impacts of climate change and management practices on crop productivity, yield, nutrient use efficiency, and soil carbon sequestration. The candidate will develop remote sensing products to understand spatial and temporal patterns of nutrient and carbon fluxes. 

(3) To collaborate with stakeholders, including farmers, policymakers, and researchers for field data collection and research dissemination. The candidate will work alongside a vibrant team of scientists dedicated to building scalable solutions for sustainable agriculture and net-zero transitions.

This Ph.D. position offers an opportunity to collaborate inter-disciplinary with other scientists on cutting-edge research in remote sensing and machine learning for climate-smart agriculture to enhance agroecosystem productivity and reduce greenhouse gas emissions.

• 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:
We are searching for a highly motivated candidate who has an M.Sc. degree in geoinformatics, remote sensing, agriculture, environmental sciences, data sciences, geography, ecology, or closely related fields. 

Demonstrated oral and written communication skills in English are required. The applicant must be able to present results at international conferences and publish in international peer-reviewed journals. The applicant should be enthusiastic about working in an international and interdisciplinary academic environment. Applications from women and people from underrepresented groups are strongly encouraged. Further, we will prefer candidates with some of the following qualifications:

• Advanced Programming & Big Data: Strong programming skills (preferably in Python) and experience handling large-scale, multi-source remote sensing datasets and cloud-computing platforms.
• Rich experience in satellite remote sensing for crop nitrogen and yield predictions. Good scientific and technical writing skills.
• Strong skills in programming (preferably in Python), large-scale remote sensing data processing, radiative transfer modelling and deep learning. Direct experience or strong background in deep learning or knowledge-guided machine learning.
• An ability to communicate effectively in English, and will contribute to dissemination, teaching and reporting research outcome in high-impact scientific journals.
• An ability and interest to collaborate across disciplinary.
• Collaborative and interpersonal skills and will contribute positively to the social working environment.

Place of employment and place of work:
The place of employment is Aarhus University, and the place of work is Ole Worms Allé 3, Aarhus 8000, Denmark. 

Contacts:
Applicants seeking further information regarding the PhD position are invited to contact: 

• Associate Professor Sheng Wang, swan@agro.au.dk (main supervisor)
• Professor Klaus Butterbach-Bahl, klaus.butterbach-bahl@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:

• admission.gradschool.tech@au.dk 

How to apply:
Please follow this link to submit your application.
 
Application deadline is 3 August 2026 23:59 CEST. 

Preferred starting date is 1 November 2026.

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.