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Field
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working with our multi-disciplinary cancer specialty clinics and tumor boards. This individual will be expected to develop algorithms around national guidelines for disease specialties including hematology
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microbiomes to adapt to environmental change. Ancient environmental DNA (eDNA) provides a unique record of past ecosystems, preserving genetic traces of microorganisms and plants that interacted with crops and
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Intelligence (AI) algorithms, including Machine Learning (ML) and Deep Learning (DL) techniques, for advanced signal analysis. The work will focus on developing methodologies for the detection, extraction
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 2 months ago
periconception through aging. Our Mission is to lead precision nutrition research through understanding how genetics and environment affect an individual’s requirements for and responses to nutrients. NRI
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Postdoctoral Scholar to support the Center's mission to develop and exploit novel sensing technologies and the algorithms to analyze their signals for monitoring geohazards. Reporting to the Center Director and
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advance pediatric, adolescent, and young adult cancer care using cutting-edge computational biology approaches. We strive to understand the germline genetics and tumor genomics of pediatric cancer to inform
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management reporting needs. Partner with programmers to design and institutionalize accurate forecasting and financial planning tools; this includes modeling new algorithms, creating functional specifications
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not intended as a deep theoretical approach to machine learning. Students will finish the class with a basic understanding of how to execute predictive analytic algorithms, as well as rigorously test
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of how your scholarship or teaching has engaged meaningfully with the mathematics underlying machine learning or AI – for example, stochastic optimization and sampling algorithms, high dimensional
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mobility needs and motivations based on the travel data, we apply different clustering algorithms (e.g., traditional k-means, density-based clustering, or neural networks). Non-negative tensor factorization