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of soil health and nutrient acquisition Proficiency in Microsoft Office, data analysis using R and SAS. Basic knowledge of remote sensing application to quantify carbon sequestration is desirable
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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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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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or R for data analysis and processing. Excellent communication skills and the ability to work effectively in a multidisciplinary team environment. Physically fit and willing to engage in extensive
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learning; Proficiency in programming languages such as Python and R. Strong experience working with climate and remote sensing datasets for environmental applications. Experience with high-performance
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programming languages (e.g., Python, R). Expertise in molecular biology techniques such as PCR, qPCR, and gene editing. Familiarity with statistical tools and software for GWAS analysis. Contract Details