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goal of this project is to develop machine learning techniques to improve climate change simulations. M²LInES is composed of more than 30 scientists at NYU, Columbia, MIT, Princeton, GFDL, NCAR and CNRS
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statistics and evaluating advisees' chances of obtaining admission. Assisting advisees with the law school application process, inclusive of personal statements, letters of recommendation, and taking the LSAT
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-Hill, Houghton-Mifflin, Macmillan, MIT Press, NYU Press, Oxford University Press, Princeton University Press, O'Reilly & Associates, University of California Press, Thames & Hudson, the American Society
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techniques; and calculation and interpretation of mathematical formulas such as percentages, ratios, statistical average, median, and multiple regressions. Advanced proficiency level in Microsoft Excel
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grammar in embryogenesis and cancer development (please visit https://labs.utdallas.edu/caolab for more details). You will ideally have a strong background in bioinformatics and statistics and prior
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with CHAMPS leadership and scientific oversight team, develop and implement priority nutrition-related research questions for CHAMPS. Monitor and evaluate nutrition-related data collected in CHAMPS MITS
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with collaborators across institutions (OSU, University of Pittsburg, MIT, McGill University, University of Guelph, and University of British Columbia) but will be physically based full time at
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collaborators on these projects, including Pawan Sinha at MIT, Alireza Ramezani at Northeastern, Joo-Hyun Song at Brown University, and David Lin at Massachusetts General Hospital. The research is supported by
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. Responsible for other duties as assigned. Basic Qualifications Bachelor’s degree in economics, data science, computer science, statistics, information systems, or related field. Experience with cleaning and
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) Additional Qualifications and Skills The following job-specific skills and competencies are preferred: Master's degree preferred Demonstrated ability to apply statistical approaches to analyze data, interpret