Forest Remote Sensing Researcher - Biodiversity Mapping

SLU - Swedish University of Agricultural Sciences; Umeå kommun; On-site; SEK 520,000 - 750,000; Full time

Job summary

The Department of Forest Resource Management at SLU in Umeå seeks a researcher with expertise in forest remote sensing and data-driven approaches for large-scale biodiversity and ecosystem monitoring. You will develop methods to map species and habitats across Europe, integrating multiple data sources and applying ML with uncertainty estimation.

The role emphasizes collaboration, methodological development, and contributing to European biodiversity assessments within an established research

Qualifications

• A doctoral degree in forest science, ecology, remote sensing, environmental science, or related field.
• Expertise in forest remote sensing and forest ecosystem analysis.
• Experience working with satellite time series and remote sensing data.
• Experience integrating multispectral, LiDAR, and field data.
• Experience applying machine-learning methods to forest ecosystems, including species and habitat mapping.
• Ability to integrate remote sensing information into biodiversity indicators and monitoring frameworks.
• Experience with large-scale species and habitat mapping, uncertainty estimation, and validation using independent datasets.

Responsibilities

• Develop and apply remote sensing and data-driven methods for large-scale biodiversity and ecosystem monitoring.
• Integrate forest disturbance information into Essential Biodiversity Variables and combine with environmental and biodiversity data to produce pan-European species distribution and habitat maps.
• Apply machine-learning methods with uncertainty estimation and validate results using systematic biodiversity observation networks, spatial cross-validation, and independent national and regional datasets.
• Contribute to assessing species and habitat status, identifying high nature value forests and degraded habitats, and prioritising areas for conservation and restoration.
• Contribute to the development of scalable biodiversity monitoring and integrated European biodiversity assessments.

Skills

Forest remote sensing

Satellite time series

LiDAR integration

Multispectral data

Machine learning in forests

Ecological data integration

Uncertainty estimation

Spatial validation

Education

Doctoral degree

Job description

The Department of Forest Resource Management at SLU in Umeå seeks a researcher with expertise in forest remote sensing and data-driven approaches for large-scale biodiversity and ecosystem monitoring. You will develop methods to map species and habitats across Europe, integrating multiple data sources and applying ML with uncertainty estimation.

The role emphasizes collaboration, methodological development, and contributing to European biodiversity assessments within an established research