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environmental impacts (e.g., greenhouse gas emissions and impacts to air and water quality). Interest in spatially explicit environmental impact assessments at regional and local scales. Proficiency in R, Python
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Engagement with Industry Partners and Scientific Community – 10% Requirements Ph.D. in Atmospheric Sciences, Climate Science, or related field. Proficiency in scientific programming (Python, R, MATLAB
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studies. Strong background in AI/ML fundamentals and extensive experience with deep learning (DL) methods. Demonstrated proficiency in Python and machine learning frameworks (e.g., PyTorch, Jax, scikit
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– 10% Requirements Ph.D. in Atmospheric Sciences, Climate Science, or related field. Proficiency in scientific programming (Python, R, MATLAB, or equivalent) is required. Experience with atmospheric
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environmental impacts (e.g., greenhouse gas emissions and impacts to air and water quality). Interest in spatially explicit environmental impact assessments at regional and local scales. Proficiency in R, Python
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experience with deep learning (DL) methods. Demonstrated proficiency in Python and machine learning frameworks (e.g., PyTorch, Jax, scikit-learn) applied to genomic/related datasets. Experience with sequence
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programming language (e.g. Julia, Python, etc.) required; Experience with numerical models (preferably integrated assessment and/or power systems models) required; Familiarity with data assimilation and/or
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analysis of biological datasets using R, Python, SAS, or related platforms Ability to integrate laboratory, greenhouse, and environmental datasets to support predictive analyses and IPM-focused decision
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-applied compounds • Experience with statistical modeling, experimental design, and multivariate analysis of biological datasets using R, Python, SAS, or related platforms • Ability to integrate laboratory
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-determination cascade. Proficiency in command-line bioinformatics and a scripting language for genomic data analysis (R, Python, or equivalent). Track record of first-author peer-reviewed publication (published