31 machine-learning-"https:" "https:" "https:" "https:" "https:" "https:" "University of Waterloo" research jobs at Virginia Tech in United States
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systems. • Develop and implement predictive models for packaging performance using machine learning approaches and physics-based simulations. • Investigate logistics optimization strategies for packaging
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or, preferably, scientific machine learning (SciML). • Conducting research related to the improvement of the hygrothermal properties of cross-laminated timber. Desing and perform testing and analysis crate
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optimize LIFU as a new human brain mapping tool and for translation to clinical therapies in addiction, mental health and pain. Knowledge in basic computer skills, record keeping and experience with human
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origin, political affiliation, race, religion, sexual orientation, or military status, or otherwise discriminate against employees or applicants who inquire about, discuss, or disclose their compensation
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incorporate multi-faceted computer-based reports and other materials. • Bachelor’s degree, or specialized training and/or significant experience equivalent to a degree. Pay Band 3 Overtime Status Non-Exempt
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pregnancy), gender, gender identity, gender expression, genetic information, ethnicity or national origin, political affiliation, race, religion, sexual orientation, or military status, or otherwise
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pregnancy), gender, gender identity, gender expression, genetic information, ethnicity or national origin, political affiliation, race, religion, sexual orientation, or military status, or otherwise
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, religion, sexual orientation, or military status, or otherwise discriminate against employees or applicants who inquire about, discuss, or disclose their compensation or the compensation of other employees
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orientation, or military status, or otherwise discriminate against employees or applicants who inquire about, discuss, or disclose their compensation or the compensation of other employees or applicants
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information, ethnicity or national origin, political affiliation, race, religion, sexual orientation, or military status, or otherwise discriminate against employees or applicants who inquire about, discuss, or