Postdoctoral position to develop models for planning of forest management based on high resolution data

Updated: 26 days ago

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 Inventories of Landscapes in Sweden, and Terrestrial Habitat Monitoring. The Department has approximately 100 employees. For more information visit: www.slu.se/srh .

Read more about our benefits and what it is like to work at SLU at https://www.slu.se/en/about-slu/work-at-slu/


Duties:

We are currently looking for a person with a particular interest in research within forest planning and the development of planning models for forestry based on high-resolution data. The developed models should be able to identify optimal management activities over time from a property perspective, without relying on the traditional stand division. The models should be implementable in the Heureka system. Heureka is designed for analyses of sustainable and multi-objective forestry (www.slu.se/heureka). The system includes several software and tools for simulation, optimization, GIS operations, database management, etc. The postdoc position is part of the research program Mistra Digital Forest (MDF), which supports society's transition to a sustainable circular bioeconomy. In MDF, researchers from various universities and disciplines collaborate to develop useful digital tools and automation techniques that leverage the vast amount of data available in the forestry sector. More information about MDF can be found at www.mistradigitalforest.se/. 


Qualifications:

You should have a doctoral degree in forest planning, mathematics or forest management with a keen interest in forestry issues and forest planning. Experience in working with optimization methods, heuristic methods, and computer-based decision support systems in general, and the Heureka system in particular, is a merit. Significant importance is placed on personal qualities such as analytical and problem-solving skills, the ability to work independently and collaboratively. Good proficiency in written and spoken English is a requirement. As postdoctoral appointments are career-developing positions for junior researchers, we are primarily looking for candidates with a doctoral degree that is three years old at most.


Place of work:

Umeå


Form of employment:

Temporary employment, 24 months.


Extent:

100%


Starting date:

According to agreement.


Application:

We welcome your application no later than 2024-01-31, use the button below.


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.

Contact person

URL to this pagehttps://www.slu.se/en/about-slu/work-at-slu/jobs-vacancies/?rmpage=job&rmjob=9309&rmlang=UK



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