PostDoc in forest remote sensing

Department of Forest Resource Management
The Department of Forest Resource Management conducts research and teaching within the subject areas of Forest Remote Sensing, Forest Inventory and Sampling, Mathematical Statistics Applied to Forest Sciences, Forest Management Planning, and Landscape Studies. The Department is responsible for several environmental monitoring and assessment programmes, including the National Forest Inventory, National Inventory of Landscapes in Sweden, and Terrestrial Habitat Monitoring. The Department has approximately 100 employees. For more information visit: www.slu.se/srh.

Duties:
The laser scanning technology has become important for mapping forest resources. Airborne laser scanning can now be used to measure individual trees also for large forests. The post doc will work with remote sensing methods in an interdisciplinary research project that combines remote sensing and genetics. The main goal of the project is to develop a digitized game-changing tree improvement methodology by connecting genetic sequences of individual trees with remotely sensed tree attributes. The post doc will work with developments of algorithms for automatic extraction of tree information from high resolution laser scanner data. The laser scanning data are collected from drones, helicopters or using ground-based laser scanning (mobile and stationary systems). The post doc will also create models needed for prediction of tree attributes using a combination of data sources. The candidate will evaluate and use the models together with other researchers in forest remote sensing and genetics.

Qualifications:
The position is primarily aimed at junior researchers and the applicant's doctoral degree may be maximum three years old. The applicant must have a PhD degree of relevance for analysis of remote sensing data. Aptitude for numerical analysis is important, demonstrated by the applicant in earlier projects and courses. Merits are knowledge about computational science, signal analysis, image analysis, point-cloud-processing, statistical analysis, numerical programming, and neural networks. Great emphasis is placed on personal qualities such as analytical and problem solving ability, ability to work independently and collaborative ability. Good skills in English are required.

Place of work:
Umeå.

Form of employment:
Fixed term employment of 24 months.

Extent:
100%

Starting date:
As soon as possible according to agreement.

Application:
We welcome your application no later than 2024-01-03, use the button below.

Interested applicants should submit the following:

1) Cover letter demonstrating the applicant’s motivation and interest in the topic (max 2 pages, in English)

2) C.V., including the date of disputation, the list of published work (if any), and names and contact information for three references

3) Copies of transcripts of academic records, or a link to/copy of doctoral thesis

Academic union representatives
https://internt.slu.se/en/my-employment/employee-associations/kontaktpersoner-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.