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. Proficiency in programming languages for data analysis (e.g., Python, R) and experience with machine learning, statistical modeling, and wearable sensor data analysis is desirable. We expect you to be able
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related discipline. Proficiency in programming languages for data analysis (e.g., Python, R) and experience with machine learning, statistical modeling, and wearable sensor data analysis is desirable. We
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(e.g., Python, SPEC, MATLAB, etc.) Experience with relevant sample preparation and lab-based analyses (e.g., SEM, Raman) Experience with or interest in engagement with major cultural heritage collections
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at the Kansas Geological Survey (KGS), a research and service unit at the University of Kansas , and will be co-supervised by Jim Butler (https://kgs.ku.edu/people/james-j-butler-jr ) and Geoff Bohling (https
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possess strong quantitative skills (e.g. Matlab, C++, Python). The term of this appointment is one year with the possibility of renewal contingent upon satisfactory performance and continued funding
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available in the LEAF lab at Boise State University (https://www.leaf-ecohydrology.org/), funded by the USDA Agricultural Research Service. The successful applicant will work with a collaborative team to
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strong programming skills in Python, and experience in at least one of the following areas: virtual reality development, machine learning, analyzing and modeling complex data, motion capture, character
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Massachusetts Institute of Technology | Cambridge, Massachusetts | United States | about 1 month ago
experiments to understand and improve tool performance, and – most importantly – by summarizing findings in white papers and application notes. A full job description can be found here: https://mitnano.mit.edu
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experience in doing so. This position is based at the Kansas Geological Survey (KGS), a research and service unit at the University of Kansas , and will be co-supervised by Jim Butler (https://kgs.ku.edu
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dependent educational benefits Life insurance coverage Employee discounts programs For detailed information on benefits and eligibility, please visit: http://uhr.rutgers.edu/benefits/benefits-overview