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Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID | Portugal | 3 days ago
or Geoinformatics, or related areas. Candidates will be assessed according to the project team’s needs regarding geospatial data and remote sensing for analysis, interpretation, and application in environmental
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/Biology Description: The Department is looking for a PhD student within the area of remote sensing of forest. Using remote sensing the PhD student will develop methods to quantify fire severity and analyze
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are rapidly evolving – ranging from remote sensing and automated sensors to genetic techniques and classical field-based inventories. This PhD project focuses on how biodiversity in forests can be measured
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analysis, statistical modelling or remote sensing experience with GIS, programming (R/Python) or handling large datasets demonstrated interest in method development or biodiversity research Great emphasis
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subject: Technology/Forest management/Biology Description: The Department is looking for a PhD student within the area of remote sensing of forest. Using remote sensing the PhD student will develop methods
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to develop and apply advanced remote-sensing approaches and AI-assisted image analysis to investigate the distribution, diversity, and spatial dynamics of Antarctic lichen communities, thereby contributing
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managed boreal forest landscapes. The research will be done in terrestrial ecosystems. It aims to include experimental and observational studies (e.g. using field, lab, remote sensing data) along
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hazards and assessing their risk for the society. At the same time, they are fully qualified users of remote sensing, GIS and statistictical software techniques that can be applied to geoscience and
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interest, narrowing the scope to natural or cultural sites, and integrating diverse remote sensing datasets. The supervisory team offers interdisciplinary expertise in geospatial analysis, machine learning
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Instituto de Ciencias del Patrimonio - Spanish Council for Scientific Research (CSIC) | Spain | about 2 months ago
self-generated data in the field-, and to explore the potential of remote sensing to unlock the relationship between vegetation history and the distribution of ancient economic and settlement remains