Postdoc: TLS-Based Tropical Forest Biomass Dynamics

Göteborgs universitet; Göteborgs kommun; On-site; SEK 520,000 - 680,000; Full time

Job summary

The University of Gothenburg invites applications for a three-year postdoctoral position in Tropical Forest Ecology, Terrestrial Laser Scanning and Forest Biomass Dynamics. The successful candidate will lead TLS workflows and collaborate with international partners within TWIG to quantify biomass changes in tropical forests.

Responsibilities include data acquisition, method development, and reproducible analysis pipelines, with opportunities to co-supervise MSc/BSc students and present at

Qualifications

• Doctoral degree is required.
• Excellent English communication in an international environment.
• Strong quantitative and computational skills for processing large ecological datasets.
• Experience with TLS data acquisition and processing.
• Experience with scientific programming or scripting and reproducible workflows.
• Willingness for extended fieldwork in tropical countries.

Responsibilities

• Develop, validate and apply the TLS-to-aboveground-biomass workflow that underpins TWIG.
• Contribute to TLS data acquisition at project sites and compare TLS estimates with conventional approaches.
• Quantify differences between TLS-based and traditional inventory estimates of biomass stocks and fluxes.
• Collaborate with project team, supervise students, and participate in international meetings.

Skills

English communication

Quantitative skills

TLS data experience

Programming/scripting

Fieldwork willingness

Education

Doctoral degree in Biology, Ecology, Forest Engineering or equivalent

Tools

Terrestrial laser scanning (TLS)

Job description

The University of Gothenburg invites applications for a three-year postdoctoral position in Tropical Forest Ecology, Terrestrial Laser Scanning and Forest Biomass Dynamics. The successful candidate will lead TLS workflows and collaborate with international partners within TWIG to quantify biomass changes in tropical forests.

Responsibilities include data acquisition, method development, and reproducible analysis pipelines, with opportunities to co-supervise MSc/BSc students and present at