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Field
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quantitative ecology, applied statistics, or a related field with strong background in statistics and model development. Experience with R and analyzing spatial datasets. Ability to apply quantitative methods
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experimental research, including characterizing mechanisms of plastic and e-waste degradation, genetic modification and engineering of model and non-model microorganisms, designing, troubleshooting, and
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modification and engineering of model and non-model microorganisms, designing, troubleshooting, and optimizing experiments, collaborating with other lab members to support complementary projects, participating
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communities using model and non-model organisms. The individual is required to use tools in chemical ecology, genomics, molecular biology, and AI-driven predictive modeling in the research project. Specific
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-based model for implementing similar changes more broadly. The position target start date is no later than June 1, 2026 with preference for a candidate who can start in Fall 2025 or Spring 2026
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quantitative ecology, applied statistics, or a related field with strong background in statistics and model development. Experience with R and analyzing spatial datasets. Ability to apply quantitative methods
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appreciation of others will help ensure the lab operates smoothly and remains a space for meaningful scientific discovery. Prior research experience in neuronal and immune cell model systems, the fields
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and sizes are altered by polyploidy in response to stress; be able to collaborate with teams working on other organisms (yeast, Drosophila , duckweed, Chlamydomonas , and Arabidopsis) and modelers
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selected researchers will contribute to both experimental and modeling activities involving sorption and condensation technologies, solar thermal integration, and system optimization. Responsibilities will
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; Assess the effects of organo-mineral management on soil biological parameters, including soil fauna; Predict the dynamic of OM in the future global climate change by using Soil Organic Models. Mentor