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Field
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its maintenance and safety increasingly depend on data. This PhD project will develop new methods that combine remote sensing, physics-based modelling, and Bayesian machine learning to support risk
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to support the management of forest resources and ecosystems. The PhD candidate will focus on integration of the extensive amount of data collected by forest machines with remote sensing data to further
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3 Fully Funded PhD Students positions!📍 Remote Sensing Laboratory, McMaster University, Hamilton, Ontario, Canada🗓 Start Date: Spring or Fall 2026The Remote Sensing Laboratory at McMaster
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Instituto de Ciencias del Patrimonio - Spanish Council for Scientific Research (CSIC) | Spain | 13 days 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
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, remote sensing observations, and prediction and valuation of forest functions, providing a holistic view on forests as complex systems. See the project website to find out more about the FORFUS doctoral
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this centre, we are opening a PhD position on remote sensing of mountain forest dynamics. The Technical University of Munich (TUM) is one of the leading universities globally. At the TUM School of Life Sciences
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organization. We invite applications from motivated candidates with passion and a strong interest in conducting research and innovation activities on crop modeling, remote sensing, and computer vision to predict
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the University of Zurich. Your profile Master's degree in Earth Sciences, Geography, Physics, Environmental Sciences, Meteorology, or a related field. Passion for atmospheric remote sensing, chemical
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access to state-of-the-art infrastructure. Supervision by PD Dr. Gerrit Kuhlmann, with joint affiliation to the Remote Sensing Laboratories at the University of Zurich. The PhD degree will be awarded by
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role in shaping the research direction by selecting study regions, refining analytical approaches, and integrating methods across atmospheric science, remote sensing, and epidemiology