New paradigm to disentangle hydrothermal stresses and assess regional agricultural vulnerability to drought-heatwave events
Afgrødesundhed
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 15 March 2027 or later. You can submit your application via the link under 'how to apply'.
Title
New paradigm to disentangle hydrothermal stresses and assess regional agricultural vulnerability to drought-heatwave events
Research area and project description
The Department of Agroecology at Aarhus University, Denmark, invites applications for a three-year PhD position in remote sensing and knowledge-guided machine learning to assess agricultural vulnerability to drought and heatwaves. The expected starting date is 15 March 2027. The position is supported by the Sino-Danish Center for Education and Research (SDC) and involves collaboration with Chinese Academy of Sciences, including a research stay of 12 months.
Food security, climate change and biodiversity loss represent three major environmental sustainability challenges. The Center for Landscape Research in Sustainable Agricultural Futures (Land-CRAFT), established in June 2022, with expertise in biogeochemistry, agronomy and climate-impact research. This PhD project aims to develop a knowledge-guided machine-learning framework that combines remote sensing, field observations and process-based models to disentangle interacting stresses and assess agricultural vulnerability at regional scales. The research will distinguish the effects of soil water limitation, vapour pressure deficit, and temperature on crop productivity. The resulting knowledge and methods will support early warning, precision irrigation and agricultural climate-risk assessment.
The PhD student will work on three interconnected research tasks:
1. Develop an integrated observation framework for crop drought and heat responses. Combine thermal infrared, multispectral and hyperspectral remote sensing with soil moisture measurements, meteorological observations and field data to characterise crop responses across contrasting environmental conditions.
2. Disentangle the individual and interacting effects of water and heat stress. Quantify how soil-water availability, atmospheric demand and temperature influence crop functioning and productivity, and identify the conditions under which their interactions intensify crop stress.
3. Assess regional agricultural vulnerability to compound drought–heatwave events.
Scale the identified stress-response relationships from field observations to regional assessments, identifying vulnerability patterns, critical thresholds and hotspots.
SDC is a partnership between all eight Danish universities and the University of Chinese Academy of Sciences (UCAS). It brings together Danish and Chinese research and education environments through collaborative research, joint supervision and international mobility. Participation offers the PhD student opportunities to gain research experience in both countries and build an international scientific network.
More about SDC
The student will be employed at Aarhus University, with Sheng Wang as the main supervisor with Kiril Manevski, Suxia Liu and Yongqiang Zhang as co-supervisors. During the research stay in Beijing, the student will collaborate with the hydrology and land-surface modelling group at the Institute of Geographic Sciences and Natural Resources Research, CAS. The student will contribute to SDC’s MSc educational activities. The SDC framework offers the option of pursuing a double PhD degree from Aarhus University and UCAS, subject to an institutional agreement and fulfilment of both universities’ requirements. SDC PhD framework.
For further information, please reach out swan@agro.au.dk.
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 yield prediction and stress analysis. 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:
How to apply
Please follow this link to submit your application.
Application deadline is 10 January 2027 23:59 CET.
Preferred starting date is 15 March 2027.
For technical reasons, you must upload a project description. Please copy the project description above and upload it as a PDF in the application.
Please note:
Salary and terms as agreed between the Danish Ministry of Taxation and the Confederation of Professional Unions. You will be employed as an academic staff member at basic salary grades 4–8. As a PhD fellow you will also receive a monthly non-pensionable allowance.
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.
The application must be submitted via the online recruitment system, which can be accessed under ‘How to apply’.
Title
New paradigm to disentangle hydrothermal stresses and assess regional agricultural vulnerability to drought-heatwave events
Research area and project description
The Department of Agroecology at Aarhus University, Denmark, invites applications for a three-year PhD position in remote sensing and knowledge-guided machine learning to assess agricultural vulnerability to drought and heatwaves. The expected starting date is 15 March 2027. The position is supported by the Sino-Danish Center for Education and Research (SDC) and involves collaboration with Chinese Academy of Sciences, including a research stay of 12 months.
Food security, climate change and biodiversity loss represent three major environmental sustainability challenges. The Center for Landscape Research in Sustainable Agricultural Futures (Land-CRAFT), established in June 2022, with expertise in biogeochemistry, agronomy and climate-impact research. This PhD project aims to develop a knowledge-guided machine-learning framework that combines remote sensing, field observations and process-based models to disentangle interacting stresses and assess agricultural vulnerability at regional scales. The research will distinguish the effects of soil water limitation, vapour pressure deficit, and temperature on crop productivity. The resulting knowledge and methods will support early warning, precision irrigation and agricultural climate-risk assessment.
The PhD student will work on three interconnected research tasks:
1. Develop an integrated observation framework for crop drought and heat responses. Combine thermal infrared, multispectral and hyperspectral remote sensing with soil moisture measurements, meteorological observations and field data to characterise crop responses across contrasting environmental conditions.
2. Disentangle the individual and interacting effects of water and heat stress. Quantify how soil-water availability, atmospheric demand and temperature influence crop functioning and productivity, and identify the conditions under which their interactions intensify crop stress.
3. Assess regional agricultural vulnerability to compound drought–heatwave events.
Scale the identified stress-response relationships from field observations to regional assessments, identifying vulnerability patterns, critical thresholds and hotspots.
SDC is a partnership between all eight Danish universities and the University of Chinese Academy of Sciences (UCAS). It brings together Danish and Chinese research and education environments through collaborative research, joint supervision and international mobility. Participation offers the PhD student opportunities to gain research experience in both countries and build an international scientific network.
More about SDC
The student will be employed at Aarhus University, with Sheng Wang as the main supervisor with Kiril Manevski, Suxia Liu and Yongqiang Zhang as co-supervisors. During the research stay in Beijing, the student will collaborate with the hydrology and land-surface modelling group at the Institute of Geographic Sciences and Natural Resources Research, CAS. The student will contribute to SDC’s MSc educational activities. The SDC framework offers the option of pursuing a double PhD degree from Aarhus University and UCAS, subject to an institutional agreement and fulfilment of both universities’ requirements. SDC PhD framework.
For further information, please reach out swan@agro.au.dk.
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 yield prediction and stress analysis. 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, e-mail: swan@agro.au.dk (main supervisor)
- Senior Advisor Kiril Manevski, e-mail: kiril.manevski@agro.au.dk (co-supervisor)
How to apply
Please follow this link to submit your application.
Application deadline is 10 January 2027 23:59 CET.
Preferred starting date is 15 March 2027.
For technical reasons, you must upload a project description. Please copy the project description above and upload it as a PDF in the application.
Please note:
- Only documents received prior to the application deadline will be evaluated. Thus, documents sent after deadline will not be considered.
- 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.
Salary and terms as agreed between the Danish Ministry of Taxation and the Confederation of Professional Unions. You will be employed as an academic staff member at basic salary grades 4–8. As a PhD fellow you will also receive a monthly non-pensionable allowance.
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.
The application must be submitted via the online recruitment system, which can be accessed under ‘How to apply’.
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