Postdoctoral position in Remote Sensing of Forest Natural Disturbances

Swedish University of Agricultural Sciences
May 30, 2024
Offerd Salary:Negotiation
Working address:N/A
Contract Type:Other
Working Time:Negotigation
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Department of Forest Resource Management The Department of Forest Resource Management conducts education and

research in the areas of forest planning, forest remote sensing, forest inventory and sampling, forest mathematical statistics and landscape studies. The department is also responsible for implementation of the ongoing environmental analysis programs National forest assessment, National targeted forest damage inventory, National inventories of the landscape in Sweden, terrestrial habitat follow-up and the butterfly and bumble bee inventory. In the business, research and environmental analysis are combined in interdisciplinary projects, which provides unique opportunities to develop overall concepts for sustainable use of the natural resources. In total, we have approx. 100 employees and during the summer half an additional approx. 80 seasonal employees in our field inventories. More information can be found at www.

Read more about our benefits and working at SLU by visiting: https: // www.

About the position

Global warming has triggered forest abiotic and biotic disturbances to an unprecedented intensity in Europe in recent years. Windstorms, drought, insect outbreaks, and forest fires are exacerbated by extreme weather, weakening the forest ecosystem and devastating the sustainable management of forest resources. Such abiotic and biotic threats to forests caused by global warming highlight the urgent need to monitor forest health and disturbance. The postdoctoral project will develop cutting-edge remote sensing techniques and methods for monitoring forest natural disturbance such as bark beetle attacks and drought stress. The potential remote sensing data include multispectral and hyperspectral drone images, optical satellite images, and laser scanning data. The work will include developing automatic methods to extract information from remote sensing data and statistical methods to estimate damages. The analysis will be applied from single trees to landscape scales. New methods and frameworks will be proposed to adapt to the new generation of remote sensing data and new needs under climate issues.

The position is supported by Horizon project RESDINET and SLU Forest Damage Center. RESDINET (https: // is a network project for novel remote sensing technologies in forest disturbance ecology, with collaborators from several departments at SLU, Finnish Geospatial Research Institute, the University of Eastern Finland, and the Slovak Academy of Sciences. The SLU Forest Damage Centre is (https: // www. Projects/slu-forest-damage-centre/) initiated by a government commission to prevent, monitor and develop knowledge for managing forest damage. The SLU Forest Damage Centre aims to lead knowledge development in forest damage issues in Sweden and ensure that scientific results and data are known and utilized in society.

We are looking for a colleague who is ambitious in technical development and highly motivated to continue an academic career in remote sensing of forest disturbances. We expect you to develop innovative research and report findings in high-impact scientific journals. We expect you to network and collaborate with remote sensing experts outside the group and scientists from other disciplines related to the topic. We also expect you to play an active role in developing the research environment.

Your profile

The position is intended for a researcher early in their career and we are primarily looking for candidates with doctoral degree issued no more than three years ago. A doctoral degree is required in relevant areas such as remote sensing, forestry, ecology, agriculture, and computer sciences. Experiences in scientific programming and remote sensing data processing and analysis are required, as well as fluent in English for communication and scientific writing. Knowledge and experience in drone imagery, multispectral and hyperspectral imagery, spectral analysis, time-series analysis, change detection, upscaling, data fusion, forest pests and diseases, environmental modeling, machine learning, and statistics are meritorious, as well as the ability of fast learning and critical thinking.

The assessment will put particular emphasis on (1) your scientific proficiency in technology and engineering subjects that are relevant to the position, (2) your ability to develop independent research and answer scientific questions, (3) your ability to collaborate and complement the ongoing research within the group. We also put great importance on personal qualities, such as teamwork, problem-solving, coordination, leadership, communication, executive skills, and independence.



Form of employment:

Temporary employment 24 months.



Start date:

As agreed. Preferably starting in autumn 2024.


Please submit your application before deadline 30 May 2024. You can submit your application by clicking the button below.

Union representatives:

https: // vid-rekrytering/

The Swedish University of Agricultural Sciences (SLU) has a key role in the development for sustainable life, based on science and education. Through our focus on the interaction between humans, animals and ecosystems and the responsible use of natural resources, we contribute to sustainable societal development and good living conditions on our planet. Our main campuses are located in Alnarp, Umeå and Uppsala, however, the university also operates at research stations, experimental forests and teaching sites throughout Sweden.

SLU has around 3,000 employees, 5,000 students and doctoral students and a turnover of over SEK 3 billion. We are investing in attractive environments on all of our campuses. We strive to provide a work environment characterised by inclusivity and gender equality, where different experiences generate conversations between people and pave the way for science, creativity and development. Therefore, we welcome applications from people with diverse backgrounds and perspectives.

Contact person

Langning Huo

Project leader, Researcher

+46 90-786 85 24

[email protected]

Jonas Bohlin

Head of Forest Remote Sensing Division

+46 90-786 86 40

[email protected]

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