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engineers to investigate the validity of data-processing workflows, evaluate effective tutoring moves using the MTM dataset, and share innovations and best practices for analyzing tutoring data at scale. NTO
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. The research team works closely with NTO engineers to investigate the validity of data-processing workflows, evaluate effective tutoring moves using the MTM dataset, and share innovations and best practices
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characteristics. Nominate and help evaluate promoter regions and candidate genes to enhance nitrogen use efficiency. Apply machine learning models to classify molecular variants as functional and assess
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an incentive when they purchase fruits and vegetables. We are evaluating various modalities of DUFBNY (e.g., community support agriculture, online shopping). To learn more visit https://doubleupnys.com/ and
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. The incumbent will join a research group led by Dr. Dena J. Clink to develop, evaluate, and apply quantitative methods for large-scale biodiversity monitoring and conservation. The research will leverage existing
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. The incumbent will join a research group led by Dr. Dena J. Clink to develop, evaluate, and apply quantitative methods for large-scale biodiversity monitoring and conservation. The research will leverage existing
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been used to evaluate various feeding and management conditions for GHG emissions and the reduction of urinary and fecal N and P excretion (Van Amburgh et al., 2019). We are seeking a highly motivated
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root architecture and soil characteristics. Nominate and help evaluate promoter regions and candidate genes to enhance nitrogen use efficiency. Apply machine learning models to classify molecular
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or evaluating methodologies for cleaning, annotating, and privacy-protecting student tutoring data to promote actionable insights at scale from extant tutoring data Experimental/quasi-experimental design and
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. The candidate will evaluate plant phenotypes, sample plant tissues, perform DNA extractions and metabarcoding library preparation, and analyze microbiome data. The candidate will also perform quantitative trait