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biomarker data. Develop predictive models and algorithms to identify risk factors, disease markers, and potential therapeutic targets for Alzheimer’s disease. Implement machine learning models to improve
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to the investigation of protein design and protein language models using advanced computational approaches. This position will also be responsible for lab management, supporting day-to-day activities and participating
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patient-specific, predictive models using real-world clinical data. The project aims to enhance understanding of disease trajectories, optimize treatment strategies, and support real-time clinical decision
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data processing and predictive modeling. REDCap integration systems for clinical research interoperability. JSON-RPC server environments for blockchain-based and internal healthcare data exchange
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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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modeling, machine learning, and data visualization Certifications/Licenses Required Knowledge, Skills, and Abilities Experience with AI-aided analytics for pattern recognition and predictive insights is
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patient-specific, predictive models using real-world clinical data. The project aims to enhance understanding of disease trajectories, optimize treatment strategies, and support real-time clinical decision
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decision-making. Leads the Data Strategy and Institutional Analytics team, driving innovation, supporting institutional priorities, and building advanced capabilities in predictive modeling, AI, and machine
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medicine offers a framework to understand the origins of disease, improve predictive models, and develop more durable therapeutic interventions. Faculty will catalyze research and teaching around
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Infrastructure and Transportation (CAIT) invite applications for a Postdoctoral Associate position in the area of monitoring and modeling of flood hazard with applications in flood early warning systems, flood