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Field
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learning including reinforcement learning, nature inspired algorithms, deep learning, agent based modeling, and natural language processing. We are specifically interested in research focused
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building sensors, analyzing data, and writing data summaries. The position is 35 hours per week for a three week duration (7/7 – 7/25). Duke University is an Affirmative Action/Equal Opportunity Employer
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candidates whose work lies at the intersection of statistics, machine learning, data analytics and modern AI algorithms. This includes, in particular, statistics for high-dimensional and complex data
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collection methods for external data (e.g. web scraping) to collect data for use in modelling and analysis. Develop analytic plans, engineer supporting algorithms, write new functions or applications in
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software Replace faulty components (e.g., contractors, capacitors, sensors) Monitor System Performance Check air flow, temperature splits, and system efficiency Log system pressures, amperage, and voltages
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and foster economic opportunity in Arizona and across the globe. This role supports irrigation research through field and laboratory work, primarily focused on soil and plant sampling, sensor
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algorithms for very high speed coherent passive optical networks (VHSP) Implementation of DSP algorithms in MATLAB/C++, that can be used for ASIC development Development of our DSP software tools Research work
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nanocrystal morphology and optical property characteristics. The researcher will work collaboratively with graduate student(s) to design and implement a machine learning (ML) algorithm using the database as
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Overview This 6 month post is associated with an i4i FAST grant in partnership with an award-winning medical tech company, WalkWithPath. The grant is titled “Step-sensor: Can sensor-based insoles
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data retrieval, interface with multiplexers and sensors. Demonstrated proficiency with eddy covariance instrumentation, and ecophysiological field instrumentation. In particular, candidate has worked