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. Develop workflows in R, Python, or MATLAB to process and analyze ocean color data, with a focus on chlorophyll-a, suspended particulate matter, and colored dissolved organic matter (CDOM). Assess the impact
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. Experience with handling large geospatial dataset using High performance computing (HPC) Advances programming (e.g., Python, R) and GIS tools (e.g., QGIS) experience. Excellent communication skills. Strong
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on analyzing satellite-derived data (Sentinel-3, Landsat) to monitor coastal ecosystem changes. Develop workflows in R, Python, or MATLAB to process and analyze ocean color data, with a focus on chlorophyll-a
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for metagenomic and transcriptomic data analysis (e.g., QIIME, DADA2, R, Python). Demonstrated ability to independently design and conduct experiments, analyze data, and publish results. Excellent written and
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Pursue research support including submission of proposals and contact with funding organizations. Communicate with all stakeholders including R&D peers, suppliers, and the client.
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apportionment, and related analytical methods (e.g., receptor models, chemical transport models, statistical analysis). Proficiency in programming languages (e.g., R, Python, MATLAB) and familiarity with relevant
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like Pandas, NumPy, SciPy, GeoPandas, etc.), and R. • Advanced skills in predictive modeling and machine learning, particularly for multi-variable simulations. • Knowledge of complex systems
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and regional scales. Proficiency in programming (e.g., Python, R) and experience with machine learning for geospatial data analysis. A strong track record of publishing research articles in high-impact
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., Python, R) and GIS tools (e.g., QGIS) experience. Excellent communication skills. Strong publication record related to current position
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multispectral/hyperspectral data processing. Proficiency in programming languages such as Python or R for data analysis and processing. Excellent communication skills and the ability to work effectively in a