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patients with early DKD and matched healthy controls. ▪ Development of an AI-driven digital African twin model capturing population-specific molecular heterogeneity, disease trajectories, and predictive
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partner from data sciences provides data management and AI based Image analysis, an internal simulations group working on quantitative models to reproduce and predict experimental data, and an internal
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- Provisional Positions Department's Website: https://cosmos.ualr.edu/ Summary of Job Duties: The Extra Help Assistant will help develop socio-computational models to advance our understanding of cyber campaigns
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California State University, Long Beach | Long Beach, California | United States | about 22 hours ago
or conference presentations in healthcare finance, healthcare risk management, health economics, reimbursement, cost modeling, risk forecasting, or financial decision-making in health care systems, patient safety
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, health and environmental stimuli jointly determine how animals function, adapt and contribute to ecosystems. PhD: Development of AI Models for prediction of resilience and susceptibility infectious
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trends and composition analysis, refractive index determination, and morphology for applications such as environmental monitoring, nuclear non-proliferation, and improving predictive modeling tools (e.g
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simulations of compact binaries (including, for example, binary black holes, binary neutron stars, and black hole–neutron star binaries). The broader goals are to generate accurate predictions for gravitational
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financial planning and predictive modeling to inform strategic growth, program viability, and resource allocation. Set Continuum-level financial targets and guardrails (e.g., administrative budgets, reserves
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the direction of the Principal Investigator in building a first-of-its-kind Software as a Medical Device (SaMD) that predicts, detects, and manages SSIs by fusing RGB + thermal wound images
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- specific predictive models, the lack of explainability in AI-driven decision processes, and the difficulty of capturing long-term dependencies in time-series data. In this project, you will focus