Postdoctoral position in ecological modeling of environmental adaptation in natural forests

Updated: 3 months ago

The Department of Forest Genetics and Plant Physiology was founded in the late 1970s - when the College of Forestry moved to Umeå. The number of employees has since grown steadily is now around 100, including postdoctoral researchers and postgraduate students. In the late 1990s it was decided to join with the Department of Plant Physiology at Umeå University to form a research center, Umeå Plant Science Centre (UPSC). The Department of Forest Genetics and Plant Physiology moved into the premises adjacent to the partner department and together have developed a close and successful collaboration on research issues, technology platforms, and training of master's and doctoral level students. The international element within UPSC is large, with over 40 nationalities represented. The department conducts introductory and advanced training in plant physiology, ecophysiology, plant molecular biology, forest genetics and forest biotechnology within the Forestry program and at the master level. The department offers postgraduate studies in biology, specializing in plant physiology, ecophysiology, plant molecular biology and forest genetics. Postgraduate courses are generally held in cooperation with the Department of Plant Physiology. For more information about the Department of Forest Genetics and Plant Physiology and UPSC visit

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The employment is part of the project Genetic basis of adaptive response in conifers, which aims to understand the genetic basis of climate adaptation in conifers, and in an applied context, predict individuals that can make locally adapted populations more resistant to changing climates.

The postdoc will test growth models and sampling approaches as part to understand adaptation to changing environments in conifers. The postdoc is also expected to participate in field sampling and maintenance and generation of CNNs for increment core analysis.


The applicant should hold a PhD in ecology, biology or equivalent. We are looking for highly motivated and team-oriented candidates with documented experience in regression modeling with tree-ring data and dendroecological fieldwork.  Experience in Python and machine learning for computer vision is a obligatory, experience in modeling tree growth using artificial neural networks is an advantage. Documented statistical and computational skills are prerequisites for the position. Very good skills in written and spoken English is obligatory.

A position as a postdoctor is intended for a researcher early in their career, we are therefore primarily looking for candidates who completed their doctoral degree no more than three years ago.

Place of work:

Department of Forest Genetics and Plant Physiology, SLU, Umeå (Sweden) 

Form of employment:

Temporary employment 24 months, with the possibility of extension.



Starting date:

According to agreement. 


We welcome your application no later than 2023-11-27, use the button below.

Academic union representatives:

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.

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