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Field
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consisting of Cornell and agency scientist. Specifically, the individual will: 1) Analyze acoustic data with existing software (Echoview, R, Python). 2) Collaborate with USGS scientists on field data
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package development and maintenance in R; record linkage/entity resolution; data privacy techniques; large data processing and high performance computing; advanced causal inference and statistics; computer
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background in machine learning, predictive modeling, or applied AI Proficiency in Python and/or R; experience with libraries like scikit-learn, XGBoost, TensorFlow. -Experience working with real-world datasets
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, and statistical analysis. Proficiency in data analytics, visualization. Proficiency in at least one of the following programming languages: R or Python. Proficiency in Microsoft Office (including
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, the individual will: 1) Analyze acoustic data with existing software (Echoview, R, Python). 2) Collaborate with USGS scientists on field data collections. 3) Investigate the spatial patterns of fish and
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have a Ph.D. in economics, public policy, education, or a related field by the start date, strong quantitative and econometric skills, experience coding (in Stata, Python, R, and/or SAS), and an interest
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(e.g., R, SAS, Python, or similar). Equipment Used: standard research equipment such as light emitting diodes, data logger, environmental sensors, LI-COR gas exchange system, fluorometer. Part time
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within an interactive research group consisting of Cornell and agency scientist. Specifically, the individual will: 1) Analyze acoustic data with existing software (Echoview, R, Python). 2) Collaborate
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of appointment. The ideal candidate will demonstrate: Strong quantitative and spatial analytic skills, with proficiency in R and Python for data management, modeling, and visualization. Experience
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of Interest To start the Online Application process for this position, click the "Apply for This Position" button located below the Contact Information. Contact Information Contact:Erin R Curry - erin-curry