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multi-source datasets and develop predictive models to support crop monitoring and agricultural decision-making. 25% – Sensor Systems and Ground-Based Platform Development Contribute to the design
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and the possibility of renewal. Dr. Fonseca’s research focuses on identifying early predictive markers of dementia, understanding mechanisms of cognitive decline, and advancing inclusive approaches to
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). Recover and characterize carbonate minerals formed during freezing using mineralogical and microscopic technique. Develop and parameterize a predictive kinetic framework using time-resolved geochemical
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fragmented between disciplines. We aim to overcome these bottlenecks to accelerate the development of sustainable processes. For this purpose, this project will develop predictive models, ranging from
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integrates predictive analytics, pharmacoepidemiologic approaches, and stakeholder-engaged methods to generate actionable evidence that informs clinical practice, policy, and interventions to improve
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interprets patient-level data to support the development of AI/ML/NLP algorithms for clinical applications. Annotates medical notes and datasets to facilitate training and validation of predictive
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and data fusion, agent-based modeling and digital twins, and predictive analysis for environmental and health applications. We are committed to recruiting and retaining highly motivated, creative
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microscopic processes with the macroscopic behavior of both engineering and natural systems and develop predictive tools for mechanical failure. Our team is highly interdisciplinary and international, bringing
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Postdoctoral Research Associate to lead the field pathology and pathogen genomics of a project building predictive tools for cotton soil-borne disease management. The work is supported through a cooperative
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Postdoctoral Research Associate to lead the field pathology and pathogen genomics of a project building predictive tools for cotton soil-borne disease management. The work is supported through a cooperative