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microenvironment, and other biological processes. Conduct preclinical studies using in vivo disease models (cancer, inflammation, organ injury, etc.) and new alternative methodologies (advanced biological models
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on developing advanced machine learning models to quantify phenotypic traits of crops, including corn, soybean, and other selected species. These models will leverage data collected from various sources, such as
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modeling, environmental simulations, and digital twin systems. -Develop analytical tools, visualization platforms, and decision-support dashboards to improve research outcomes. -Ensure data quality through
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these systems and accurate and scalable optical performance models will be investigated with the aim to gain critical insight on the most adequate solutions to accommodate future capacity requirements in optical
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Job Purpose The candidate will contribute to the work of the consortium *Policy Modelling for Health (HealthMod”, 2024-2028) and associated projects, *working with Dr. Andreas Hoehn, Prof. Petra
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approaches (e.g., agile methods, model-based development, CI/CD pipelines) in concrete research projects. Publication of research results at national and international conferences. Assistance in preparing
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computational models of the immune response for multi-scale epidemic models. This position offers an excellent opportunity for recent graduates interested in applying quantitative and computational methods
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large language models, to develop new hypotheses and predictive models for unique health conditions. Experience with obesity intervention trials in children is preferred. In partnership with Children’s
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The Department of Biostatistics & Bioinformatics at Duke University invite applications for a postdoctoral associate position in mathematical modeling, as part of a new NIH-funded Center for Excellence in
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patient samples. The Sheffield arm of the project will develop statistical and machine learning models to identify and validate predictive biomarkers of resistance evolution in Pseudomonas aeruginosa lung