108 computer-algorithm "Integreat Norwegian Centre for Knowledge driven Machine Learning" Fellowship positions at Zintellect
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the guidance of a mentor, this opportunity will involve: developing and applying methods in computational biology and artificial intelligence to gather information about gene function in the legume family; using
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-ARS Ornamental Research Program in Miami, FL. The fellow will participate in a team effort to maintain and characterize Ornamental Genetic Resources (OGRs) by discovering molecular resources using
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affect oyster phenotypes targeted for improvement. The fellow will also gain experience using advanced computational methods to develop tools that can accurately predict desirable phenotypes. With
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Program of the USDA ARS offers research opportunities to motivated postdoctoral fellows interested in solving agriculture-related problems at a range of spatial and temporal scales, from the genome
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for Physical Sciences Qubit Collaboratory (LQC) is a national Quantum Information Science Research Center hosted at the Laboratory for Physical Sciences (LPS) at the University of Maryland, College Park. The LQC
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areas. These include, but are not limited to: Applying machine learning algorithms to solve real-world problems. Creating and structuring databases for storage, retrieval, and image analysis. Determining
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. Scientists in this unit maintain a comprehensive IAV research program including investigation of virulence mechanisms, vaccinology, immunology, and virus evolution. The participant will be based
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validate algorithms for estimating heat stress, counting animals, and estimating mass in real-time. Although research is needed to integrate One Health assessments across the soil-pasture-animal continuum
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Requirements: This opportunity is available to U.S. citizens only. ORISE Information: This program, administered by ORAU through its contract with the U.S. Department of Energy (DOE) to manage the Oak Ridge
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, quantitative genetics, physiology, biotechnology, computational biology, and horticulture. The participant will be encouraged to establish robust collaborations with faculty at Cornell University, Cornell Agri