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. Opportunities to Contribute Develops dynamic river‑lake network models to assess geochemical and ecological changes—including carbon cycling and elemental fluxes—resulting from enhanced rock weathering. Writes
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, empirical modeling and methods, and related areas. Preferred Qualifications Strong interest in international business and global /cross-border supply chain analytics and associated policies is highly desired
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biological questions. Opportunities to Contribute Conduct research in the area of statistical modeling for single-cell multi-omic data. Perform clustering, differential expression analysis, predictive modeling
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initial problem specification, data gathering and analysis, model creation, and implementation Strong understanding of artificial intelligence applications and methodologies, such as working knowledge
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-based perturbations, base/prime editing, and targeted epigenetic modulation). Functional genomics in neuronal systems, including transcriptomic and epigenomic profiling. Model systems such as human iPSC
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atomistic simulations, scientific machine learning, reaction modeling, and integration of computational and experimental data. The associate will develop reproducible computational workflows, collaborate with
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, ). Biochemistry, cell biology, genetically engineered mouse models and patient-derived organoids / xenografts will be employed in the study. Successful applicants will be a highly motivated individual with a recent
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the laboratory's focus on neuroimmune interactions and trauma-related physiology. Develop and implement mouse models relevant to neuroimmunology, stress biology, cardiovascular physiology, and immune-mediated
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of large-scale geospatial and time-series datasets. The candidate will develop and evaluate multimodal AI models to characterize vegetation and land-surface dynamics and quantify ecosystem responses and
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systems. In parallel, they will design and develop agentic AI and physics-aware AI models to accelerate discovery and deepen mechanistic insight in catalysis. This work will be carried out in close