Post Doctoral Researcher In Remote Sensing Of Vegetation Bolzano

Post Doctoral Researcher In Remote Sensing Of Vegetation
Bolzano
Trentino Alto Adige, Bolzano

Postdoctoral Researcher in Remote Sensing of VegetationEurac Research is an interdisciplinary research center located in Bolzano, Italy.

At the Institute for Earth Observation (EO), we monitor environmental parameters and processes using Earth observation and climate data in mountain regions.

One of our main interests is to understand and model the impacts of climate change on glaciers, snow, hydrology, soil, and vegetation.

The successful candidate will support the Eurac Institute for Earth Observations by conducting research on estimating key environmental parameters to study the impact of climate change on mountain vegetation.

The candidate will join the Biosphere and Hydrosphere research group and collaborate with other groups within the institute.

The Biosphere and Hydrosphere (BH) research group leverages Earth Observation (EO) technologies to investigate the spatial-temporal dynamics of the terrestrial water cycle, vegetation conditions, and land cover, with a particular focus on the Alps.

The group develops tailored methods to process satellite imagery, addressing mountainous regions' heterogeneity and topographic complexity.

The derived products and information are utilized for a range of hydrological, agricultural, and ecological applications.

Role Description This is a full-time on-site role as a Postdoctoral Researcher in Remote Sensing of Vegetation at the Institute for Earth Observation – Eurac Research in Bolzano.

The role involves monitoring spatio-temporal dynamics of mountain vegetation to understand their responses to biotic and abiotic factors and develop solutions in collaboration with stakeholders.

Daily tasks include:

Estimate vegetation biophysical parameters in the European Alps from multi-source satellite data.

Apply data fusion and AI techniques to integrate various data types, enhancing the spatial and temporal resolution of satellite datasets.

Validate estimates of biophysical parameters based on satellite data against in situ observations.

Analyse timeseries of vegetation biophysical parameters to detect trends and anomalies, and to study the relationship between multiple variables. Maintain thorough documentation of generated codes and ongoing progress of activities. Manage the project tasks within the institute for Earth Observation, participate in project meetings with external partners, contribute to the generation of the project deliverables and reports. Write and publish scientific papers in peer-reviewed journals.

Present research findings at international conferences and events, showcasing the project's progress and results. Work closely with the research group on overlapping topics to foster a collaborative research environment. In the case of post-docs or senior researchers, actively contribute to acquiring funds to further develop the research line. Qualifications Education: PhD in Environmental Engineering, Remote Sensing, Informatics Engineering, Geophysics, or a related discipline. Alternatively, a Master's degree in a relevant field (e. g. , Engineering, Physics, Geosciences) followed by significant work experience in remote sensing of vegetation and in modeling and monitoring environmental processes. Experience: Proven experience in processing optical and radar satellite data over wide areas. Knowledge and proven experience in methods to estimate vegetation biophysical parameters from satellite data. Demonstrated proficiency in at least one programming language such as Python or R. Proficiency in handling and analyzing geospatial data (both raster and vector formats). Familiarity with Earth observation software tools (e. g. , GDAL, SNAP). Skills in data analysis and visualization for spatial and temporal datasets. Skills: Certified B2 level of Italian or German proficiency to interact with local stakeholders. Certified B2 level of English proficiency. Strong teamwork abilities and excellent communication skills. Motivation to learn and adapt, with a flexible approach to work. Additional Requirements: Willingness to relocate to Bolzano or nearby cities. Capability to use HPC clusters. Knowledge of machine learning methods. Experience working with a Linux environment and command-line (shell). Knowledge of GIS Systems (GRASS software suite, QuantumGIS, ArcGIS, etc.

). Experience in managing projects or work packages.

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