Descripción
Department of Forest Resource ManagementWe are looking for a person with expertise in remote sensing and data-driven approaches to forest ecosystems and biodiversity monitoring. Are you the person we are looking for to apply and develop methods for large-scale species and habitat mapping and contribute to European biodiversity assessments?About the positionYou will work with developing and applying remote sensing and data-driven methods for large-scale biodiversity and ecosystem monitoring. Your work will involve integrating forest disturbance information into forest structure Essential Biodiversity Variables and combining these with environmental and biodiversity data to produce pan-European species distribution and habitat maps. You will apply machine-learning methods with uncertainty estimation and validate the results using systematic biodiversity observation networks, spatial cross-validation, and independent national and regional datasets. You will also contribute to assessing species and habitat status, identifying high nature value forests and degraded habitats, and prioritising areas for conservation and restoration. Through this work, you will contribute to the development of scalable biodiversity monitoring and integrated European biodiversity assessments.Your profileWe are looking for a researcher with expertise in forest remote sensing, forest disturbance dynamics, and landscape-scale ecological analysis.Requirements: A doctoral degree in forest science, ecology, remote sensing, environmental science, or a 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 spec