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Postdoctoral position

  • Yrkesroll


  • Anställning

    Heltid, 6 månader eller längre

  • Lön

    Fast månads- vecko- eller timlön

  • Publicerad

    30 januari

  • Sök jobbet senast

    1 mars

Om jobbet

Department of Forest Resource Management, SLU
The Department of Forest Resource Management conducts teaching and research in the areas of Mathematical Statistics Applied to Forest Sciences, Forest Remote Sensing, Forest Inventory and Sampling, Forest Planning and Landscape Studies. The Department is also responsible for several environmental monitoring and assessment programs, including the Swedish National Forest Inventory, National Inventory of Landscapes in Sweden, Terrestrial Habitat Monitoring and the Butterfly and Bumblebee Inventory. The work done by the Department combines research and environmental analysis in cross-disciplinary projects, which gives unique opportunities to develop holistic approaches for a sustainable use of the natural resources. At the Department there are approximately 100 employees. For more information visit:


In the 2-year project the Postdoctoral Researcher will primarily be working with the development of statistical theory for change estimation within hierarchical model-based (HMB) inferential framework using a fusion of remotely sensed data such as LiDAR data collected by NASA’s GEDI and ICESat-2 missions; airborne LiDAR data; multispectral data collected by ESA’s Sentinel-2 and NASA’s Landsat 8 missions, and other sensors. The project is financed by the Swedish National Space Agency (ref. SNSA-171/19) and will be carried out in a group of researchers at the Department of Forest Resource Management, SLU, and collaboration with United State Department of Agriculture (USDA) Forest Service, the University of Maryland, and NASA. The main objectives of the project is threefold:
  • To develop a HMB statistical framework for the change estimation of forest attributes such as biomass and volume, through fusion of different remotely sensed and field data sources.
  • To demonstrate the performance of the HMB-methods through case studies utilizing a combination of different remotely sensed data.
  • To evaluate under what conditions the HMB method for change estimation is to be preferred over other methods, through analytical and empirical comparisons.


As postdoctoral appointments are career-developing positions for junior researchers, we are primarily looking for candidates with a doctoral degree that is preferably within three years of the application date (parental leave disclosed from the accounted time period). The PhD degree should be in remote sensing or related forest sciences, forest biometrics or a related discipline but with main focus on forest attributes assessment.

Other required qualifications are

1) proven research productivity with publications in the peer-reviewed literature

2) experience of forestry analytics, using preferably R programming language and/or GIS software

3) good communication skills with fluency in English (both written and oral).

Proven experience in working within Bayesian model-based inferential framework is a merit.

Place of work:


Form of employment:

Temporary employment, 24 months



Starting date:

1 April 2020 or according to agreement


We welcome your application no later than 2020-03-01, use the button below.

The application must contain:

- CV including a summary of the research experience,

- contact information to two reference persons.

Academic union representatives:

The Swedish University of Agricultural Sciences (SLU) develops the understanding and sustainable use and management of biological natural resources. The university ranks well internationally within its subject areas. SLU is a research-intensive university that also offers unique degree programmes in for example rural development and natural resource management, environmental economics, animal science and landscape architecture.

SLU has just over 3,000 employees, 5,000 students and a turnover of SEK 3 billion. The university has invested heavily in a modern, attractive environment on its campuses in Alnarp, Umeå and Uppsala.

SLU is an equal opportunity employer.


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