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Competencies Prior research assistantship(s) in economics, public policy, or related quantitative social science fields. Advanced training in econometrics, including causal inference methods. Experience
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statistical models and reproducible data processing pipelines using knowledge of best practices in machine learning and statistical inference. Serves as a single point of contact for all requests and engages
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statistical inference. Provides expertise for high level or complex data-related requests and engages other IT resources as needed. Analyzes moderately complex data sets for the purpose of extracting and
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statistical inference. Provides expertise for high level or complex data-related requests and engages other IT resources as needed. Partners with other campus teams to assist faculty with data science related
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of best practices in machine learning and statistical inference. Provides expertise for high level or complex data-related requests and engages other IT resources as needed. Performs other related work as
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various internal data systems as well as from external sources. Maintains and analyzes statistical models using general knowledge of best practices in machine learning and statistical inference. Performs
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/inference optimization at system level: KV cache optimization, Quantization. Strong portfolio or history of translating academic research and prototypes into robust, production-ready AI/ML solutions deployed
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after infection and vaccination, (b) examining variability in individuals’ responses after multiple exposures and inferring correlates of protection, (c) developing methods to measure vaccine
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individuals’ responses after multiple exposures and inferring correlates of protection, (c) developing methods to measure vaccine effectiveness in different populations, and (d) predicting pathogen dynamics
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external sources. Maintains and analyzes statistical models using general knowledge of best practices in machine learning and statistical inference. Performs maintenance on large and complex research and