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of dendrochronology techniques, from the research plan, field work and laboratory, and interpretation and publication. He/she should be comfortable with the R and/or Python languages. Experience in handling large
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and monitoring of environmental parameters; participation in processing and analysis of collected data, including the use of programming languages (Python and/or C++), GIS methods, and machine learning
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modelling tools are required. Robust modelling and programming abilities (e.g., Python) are essential prerequisites. Experience with VIC (or similar hydrologic models), GIS, and large-scale computing
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positions that will support ongoing work on peatland forests biodiversity and restoration. The primary tasks include processing GIS and remote sensing data, such as satellite and drone imagery and LiDAR data
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between 1300 and 1900 CE. A short description of the project can be found here: https://www.synergy-plague.org/research/introduction/. The project is funded through the European Research Council’s Synergy
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numerical analysis skills (e.g., Python, MATLAB) and/or experience with groundwater/geochemical modelling software (e.g., MODFLOW, PHREEQC). Experience with laboratory analytical methods (e.g., chromatography
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and applied statistics, including use of tools such as R, Python, GIS, Git or similar data-science software. Solid experience with community data and biodiversity monitoring. A broad ecological
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are seeking a GIS Technician with a good eye for detail. The ideal candidate will demonstrate proficiency in ArcGIS Pro and Online, with a preference for some experience running Python scripts. Experience with
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years prior to the effective date of appointment with a minimum of one year eligibility remaining. • Strong proficiency in Python or R and experience with High-Performance Computing. • Proficient
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applicant will be to interpret remotely-sensed imagery to label and validate polygons of disturbance in the landscapes in and around national parks of the Great Lakes region, and to manage the data in a GIS