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Field
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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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, tracking, spatio-temporal modeling, edge learning) using field data (traffic cameras, micromobility telemetry, connected vehicle/V2X, crash records, GIS). · Manage and coordinate pilot deployments
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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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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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/C++, FORTRAN and/or Python. Experience working with geo-spatial information, remote sensing data, and GIS software. Experience in deep learning and computer vision. Experience in developing software
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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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: You will teach courses in the BSc and MSc programmes in geography and will also offer courses for other programmes in the faculty that require GIS skills (e.g. MSc Oceans & Lakes, MSc Biology, MSc Urban
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). Proficiency with programming languages (e.g., R, Python, Matlab) for data management and analysis, computational social science, and/or machine learning applications. Acquisition, processing, and analysis
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specific technical knowledge (proficiency in relevant tools and methodologies, e.g., GIS, Python, IoT sensors, GPR, SAR imagery, machine learning, etc.); and (3) Interview, with respective weightings of 40
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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