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meteorological, snowpack, and avalanche datasets using statistical, geospatial, and programming tools (R and Python). Calibration, evaluation, and application of snowpack and hydrologic models (e.g., SNOWPACK
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using magnetometer data as well as exploring the potential for existing geospatial maps to enable long range, covert and autonomous navigation in underwater environments. We are seeking a postdoctoral
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information Experience working with environmental or geospatial datasets, including remote sensing, flux tower or micrometeorological data, weather or climate data, or hydrologic observations Experience
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in geospatial data analysis is an advantage. Applicants must be able to work independently and in a structured manner and demonstrate good collaborative skills. Applicants must have good written and
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platforms. Knowledge of vessel-motion prediction, dynamic obstacle avoidance, separation assurance, or traffic-aware navigation would be advantageous. Familiarity with geospatial data, maritime traffic data
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events and in machine learning for the earth system is required Strong and demonstrated programming skills are required Prior experience with geospatial data analysis in Python, working on scientific HPC
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. Demonstrated proficiency with scientific programming (e.g. Python) is an advantage. Demonstrated proficiency in geospatial data analysis is an advantage. Applicants must be able to work independently and in a
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platform for the Pan-Amazon Evidence and Action Hub that hosts diverse and harmonized sustainability-related datasets, including environmental, socioeconomic, cultural, and geospatial data. Design and
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₃ emissions affect peatland ecosystems across the island. The successful candidate will lead research integrating remote sensing, fieldwork, laboratory analysis, and geospatial methods, including GIS and
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knowledge Produce geospatial scenarios, vulnerability indicators, and decision-support tools Collaborate with research teams and community partners to support model development and application Mentor students