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The University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 3 months ago
, or other novel/emerging pollutants - Developing / implementing advance machine learning algorithms for environmental datasets - Attention to detail and careful documentation of work products such as How
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. Responsibilities include conceptualizing and implementing statistical and structural models, developing scalable algorithms for system optimization and control, conducting policy-relevant economic analysis
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the opportunity to conduct independent research and originate research topics over time Contribute to the long-term success of our research-driven algorithmic trading business Below is a list of skills and
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sustainability. The selected researcher will contribute to the development of predictive models and machine learning algorithms for data analysis from plant-based sensors, multispectral and thermal imagery, and
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and Algorithms group. The post holder will contribute to the intellectual life of the School through conducting and publishing outstanding quality research, engaging in high quality teaching, and
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nuclear and particle physics research leveraging machine learning and AI for data analysis and detector development, as well as exploratory work in quantum algorithms, depending on background and interests
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heterogeneous multi-omics datasets. Integrative Data Analysis: Perform and lead analysis of large-scale multi-omics datasets, including RNA/DNA sequencing, methylation, and metabolomics. Method Development
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tools for the prediction of composite manufacturing processes. You will work on development of algorithms, custom written codes, application of commercial finite element software and development of user
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Leave Professional Development Opportunities https://www.youtube.com/watch?v=BALBcUSl7ck Job Related Minimum Required Education and Experience Requires a bachelor’s degree in a job related field and 4
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postdoctoral researcher to join our dynamic animal science and artificial intelligence team. The candidate will develop novel algorithms that advance the use of computer vision in precision livestock farming