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of a next-generation turbidity meter (Arduino-based with radio communication to a central controller). * Develop and validate calibration methods for new sensors for turbidity and existing commercial
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from multiple systems and sources to answer key operational questions. Deep experience using a variety of data mining/data analysis methods to build and implement dashboards, models and algorithms
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central controller). ● Develop and validate calibration methods for new sensors for turbidity and existing commercial sensors. ● Explore high-frequency turbidity monitoring as a tool for assessing
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, and iterate the design of a next-generation turbidity meter (Arduino-based with radio communication to a central controller). ● Develop and validate calibration methods for new sensors for turbidity and
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and sources to answer key operational questions. Deep experience using a variety of data mining/data analysis methods to build and implement dashboards, models and algorithms that can help stakeholders
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algorithms. Excellent computer skills, including thorough familiarity with multiple programming languages, some experience in writing non-trivial programs, and familiarity with common algorithms, mathematical
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knowledge of VBA and Excel is preferred. Strong knowledge in areas of Computer Science that are relevant for financial databases and modeling, including data structures and algorithms. Excellent computer
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: Appropriate research areas may include but are not limited to: Development and utilization of rapid, inexpensive, and/or in situ sensors for real-time detection of chemical hazards e.g., allergens, heavy metals
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during food processing and storage. Chemical Food Safety : Appropriate research areas may include but are not limited to: Development and utilization of rapid, inexpensive, and/or in situ sensors for real
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of Mathematics at Cornell. Members of the lab engage in interdisciplinary research, drawing on approaches from geometry, topology, graphs and networks, probability/statistics, and algorithm design, in conversation