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Service (ARS), located in Beltsville, Maryland. The Agricultural Research Service (ARS) is the U.S. Department of Agriculture's chief scientific in-house research agency with a mission to find solutions
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: This research project aims to investigate the capabilities of long-read next-generation sequencing (NGS) technologies for adventitious virus detection in a complex matrix mimicking a biological test material. The
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a mission to find solutions to agricultural problems that affect Americans every day from field to table. ARS will deliver cutting-edge, scientific tools and innovative solutions for American farmers
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), which includes NIRSpec/BOTS transmission spectroscopy of 11 super-Earth and sub-Neptune transiting exoplanets detected by TESS. These observations will enable a range of investigations into the magnitude
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national scale programmatic decisions and policy. Specific activities include: Operationalize, and where needed, improve Bayesian spatio-temporal feral swine abundance model allowing predictions to be
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Center for Biologics Evaluation and Research (CBER) | Silver Spring, Maryland | United States | 20 days ago
, which could include Bayesian methodologies and use of artificial intelligence to systematically integrate available information for evolving benefit-risk assessment. The goal is to tackle the major
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in chemistry and biology, approaches for extracting relevant information from foundation models, and/or methods for adaptive experimental design such as active learning or Bayesian optimization
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, Artificial Intelligence , Bayesian Statistics , Big Data , Scientific Machine Learning , Social Sciences , Biomedical Informatics , Causal Inference , Computational Social Science , Data Science and
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. Explore whether the real-world evidence (RWE) approaches as well as Bayesian borrowing can help address sample size and ethical concerns for rare diseases. Collaboration between the statistician at DB9 and
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management systems. Integrate remote sensing (satellite, airborne, UAV), hyperspectral/multispectral data, and proximal sensors into modeling workflows for crop status assessment, stress detection, and yield