Institutionen för skoglig resurshushållning

The Department of Forest Resource Management is seeking a motivated researcher to drive the digitalization of forest management. The position focuses on developing and incorporating automated, cost-efficient methods for acquiring tree-level data to support precision forestry.

About the position

You will work at the interface of advanced remote sensing and practical forest management. The research involves integrating multi-source data—specifically Airborne and Mobile Laser Scanning—with operational machinery data to create actionable workflows. A distinct but complementary component of the role involves evaluating the economic benefit (Value of Information) of these new inventory methods compared to traditional approaches.

Duties and Responsibilities:

• Algorithm Development: Develop and validate workflows for estimation of forest attributes using high-resolution LiDAR data (ALS, MLS/TLS).

• Research Funding: actively lead the application process for external research funding, writing grant proposals to secure long-term project financing.

• Sector Collaboration: Collaborate closely with partners in the Swedish forest sector to ensure research relevance.

Your profile

Required:

• A PhD in Forest Remote Sensing, Forest Technology, or a related field.

• Knowledge about Nordic forestry practices, specifically mechanized harvesting and boreal management.

• Advanced programming skills in Python and R for statistical analysis and spatial data processing.

• Experience in applying for research funding or a demonstrated ability to write high-quality grant proposals.

• Demonstrated experience in coordinating data collection campaigns, processing and analyzing LiDAR data.

Merits (Desirable):

• Experience with forest decision support systems (e.g., Heureka) and economic analysis of inventory data.

• Experience in the Swedish forest sector, with a documented history of collaboration with forest companies.

• Knowledge of Deep Learning frameworks applied to forestry.

• Experience with synthetic data generation.

About us

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 the implementation of the ongoing environmental monitoring programs the National Forest Inventory, The National Inventories of the Landscapes in Sweden, Terrestrial Habitat Monitoring and the Butterfly and Bumblebee Inventory. In total, we are about 110 employees. More information can be found here.

Read more about our benefits and working at SLU by visiting: https://www.slu.se/en/about-slu/work-at-slu/

Location

Umeå

Form of employment

Indefinite-term employment. SLU may use probationary employment.

Scope

100%

Start date

As agreed. 

Application

Please submit your application before deadline 3rd of March 2026. You can submit your application by clicking the button below.

Union representatives:

https://internt.slu.se/en/my-employment/employee-associations/kontaktpersoner-vid-rekrytering/

Sveriges lantbruksuniversitet (SLU) har en nyckelroll i utvecklingen för hållbart liv, grundad i vetenskap och utbildning. Genom vårt fokus på samspelen mellan människa, djur och ekosystem och ett ansvarsfullt brukande av naturresurserna bidrar vi till en hållbar samhällsutveckling och goda livsvillkor på vår planet. Huvudorter är Alnarp, Umeå och Uppsala, men verksamhet bedrivs också på forskningsstationer, försöksparker och utbildningsorter i hela landet.

SLU har drygt 4000 medarbetare, 6000 studenter och forskarstuderande och en omsättning på över 4,5 miljarder kronor. Universitetet satsar på attraktiva miljöer på sina campusområden. Vi arbetar för en jämställd och inkluderande arbetsmiljö där öppna samtal mellan människor med olika erfarenheter lägger grunden för vetenskaplighet, kreativitet och utveckling. Vi välkomnar därför personer med olika bakgrunder och perspektiv att söka den aktuella anställningen.