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of algorithms and models to realistically simulate forest ecosystem dynamics under varying conditions of land use change, forest and land management, climate variability, and other environmental stressors
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imagery). Experience in building data models using Python or other statistical and/or mathematical programming packages. Proficiency in developing machine learning algorithms to analyze spatial-temporal
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genetic knockouts in yeast and mammalian cell lines, and protein purification. Job Responsibilities: 35%: Computational algorithm development and data analysis 35%: Design and conduct experiments with yeast
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model algorithms for livestock enteric fermentation and manure housing and management using a scientific programming language. Integrate the modules into the APEX ecosystem simulation model. Assess and
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will be published in peer-reviewed journals and technical reports, and algorithms and models will be shared with stakeholders and the scientific and forest management communities. Engage with industry
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emissions and soil health parameters. Results will be published in peer-reviewed journals and technical reports, and algorithms and models will be shared with stakeholders and the scientific and forest