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Director, Community Engagement, Constituent Engagement, Duke Alumni Engagement and Development (AED)
retirement benefits, and a wide array of family-friendly and cultural programs to eligible team members. Learn more at: https://hr.duke.edu/benefits/ Equal Opportunity Employer: Duke is an Equal Opportunity
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to the MSU Authority Having Jurisdiction governance model, and use this knowledge to better align the three efforts within the Construction Quality Assurance team to continually improve our culture, team
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Python. Other requirements to consider: Machine Learning knowledge. Specific Requirements Knowledge: Fluid Mechanics. Computational Fluid Mechanics (CFD). Aerodynamics. Wind turbines. It will be assessed
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through mass media. Ability to use the computer for program delivery and management. Ability to visit clientele at sites throughout the county. Ability to plan and teach educational programs. Demonstrated
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modeling and/or machine learning: keep accurate records of experiments and results perform data interpretation/summarization including writing custom code and application of analysis algorithms communicate
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technological change driven simultaneously by digitization, the application of artificial intelligence and machine learning to all facets of company, economic, and human data, and a new emphasis on the importance
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-Computer Interaction CAP 4104 - HCI for CS CAP 4612 - Intro to Machine Learning CAP 4630 - Artificial Intelligence CAP 4641 - Natural Language Processing CAP 4770 - Intro to Data Mining CAP 4830 - Modeling
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Postdoctoral Researcher in Natural Language Processing and Digital Humanities (18 months, full-time)
Python Documented experience with NLP and computational text analysis Experience working with language modelling, semantic analysis, or related machine learning approaches Requirements Documented
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, especially. multimodal data analysis. Experience on image processing (especially on MRI data) via machine learning. Programming skills (e.g., Python) are required. Ability to communicate effectively in both
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silico approaches. This may include mathematical modeling of biological systems, machine learning and artificial intelligence methods, and the development of innovative algorithms and software pipelines