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. Approval of remote and hybrid work is not guaranteed regardless of work location. For additional information on remote work at Penn State, see Notice to Out of State Applicants . This is a term position
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and avoid indirect land use emissions from the clearing of new forests. Requirements Programming skills, preferably in Fortran, Python / R Knowledge of remote sensing data processing and analysis
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contributing to professional growth is highly valued. Applicants with experience in forest or wildlife habitat classification using remotely sensed data will receive special consideration. Duties (%) 10% — With
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models/tools. Experience with large, varied datasets. Experience working with soil, water, and plant sensors and remote sensing technology. Other Requirements: This position requires physical activities
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traps, vegetation plots) and for ecosystem mapping (e.g. remote sensing, GIS). You have affinity with renewable energy planning, nature-positive transitions, and/or biodiversity governance. You possess
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remote sensing using active sensors. The successful candidate must have a record of publication that demonstrates a process-level understanding of the forces that shape marine cloud microphysics
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-based models, and remote sensing technologies. Required Qualifications • Ph.D. in Civil or Environmental Engineering, Hydrology, Data Science, Geosciences, Computer Science, or a related field. PhD must
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the spread of invasive species. This work will be conducted through a trait-based modelling framework, integrating remote sensing, chronosequences, field observations, and trait databases to assess how
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University of Campinas (UNICAMP) in Brazil, have an open call for 2 post-doctoral fellowships for the project “Hybrid hyperspectral-SAR remote sensing for agriculture application”, an international cooperation
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Associate to undertake fundamental and applied research into novel deep learning approaches to analysing LiDAR and vision data in forest imaging and remote sensing. The role is part of a three-year project