87 parallel-computing-numerical-methods-"Multiple" Fellowship positions at Zintellect
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computing (HPC) environments and include data assimilation techniques in a Bayesian framework. Under the guidance of a mentor, the participant will identify and integrate multiple data streams into the model
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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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. 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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-performance computing (HPC) systems for large-scale data processing, parallelized workflows, and computationally intensive analyses. Demonstrated experience applying phylogenetic and phylodynamic methods
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natural ecosystems throughout the growing season, and Assess how multiple stressors impact insects in the lab and field. The selected applicant will also have the opportunity to interact with a
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and poultry to generate knowledge and technology that reduces economic losses, prevents foodborne illnesses, and decreases animal suffering and death. Our prion research program at Virus and Prion
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excellence of our agriculture. The vision of the agency is to provide global leadership in agricultural discoveries through scientific excellence. Research Project: This appointment is part of the Methods and
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Project: The participant will have the opportunity to take part in the Methods and Applications of Food Composition Laboratory effort to improve the speed, accuracy, and/or sensitivity of methods
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of such field studies and, as they have learned with experience what the threats are in these environments and how to improve measurement ability, have modified methods. Why should I apply? As an ORISE