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methods and software, including uncertainty methods, spatialized approaches, and integration with dynamic modeling frameworks. Experience applying or developing mechanistic animal models, and/or whole farm
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program. Our work focuses on the development of advanced cancer models, integrative genomic analyses, and the discovery of novel therapeutic strategies. Using systematic, interdisciplinary approaches
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to develop chemical probes, investigate biological mechanisms, and evaluate in vivo efficacy. In particular we use the promiscuous pregnane X receptor (PXR) and constitutive androstane receptor (CAR) as models
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expensive) drugs. DESCRIPTION: This project proposes the development of an AI-driven computational pathology framework to discover biomarkers from large-scale datasets of cancer patients with clinical
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expression to identify mechanisms of acid-adaptation–driven intracellular survival. The Postdoctoral Research Associate will maintain rigorous records, write and contribute to publications and sponsor progress
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National Energy Technology Laboratory (NETL) | Albany, New York | United States | about 19 hours ago
will engage in multiscale modeling and machine learning to develop reliable, efficient framework for predicting long-term creep and fatigue behaviors of heat-resistant structural alloys considering
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, cash flows, and long-term business viability. Your Role We are seeking a highly motivated and creative postdoctoral candidate to develop data-driven financial forecasting, planning, and scenario-analysis
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the Biological, Environmental and Planetary Science Division. Advance the frontiers of structural biology by developing AI-driven methods for interpreting complex crystallographic data. This role will enable new
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techniques: identifying the factors that establish early RT at target genes, determining how they promote translocation biogenesis, and testing them in preclinical models. The work combines CRISPR engineering
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associates in Artificial Intelligence (AI) in Biomolecular Modeling. The postdoctoral associate will focus on developing and applying AI methodologies to drive advances in drug discovery and biomolecular