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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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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 12 hours ago
with experience in causal inference predictive modeling, and data linkages will be given preference. Preferred candidates will have a strong publication record for their career stage, strong oral and
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, administrative databases, clinical studies, and patient networks. - Development of predictive and risk models based on Real World Data. - Ensuring compliance with regulatory standards (EMA, FDA, etc.) in the use
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. The successful candidate will contribute to interdisciplinary collaborations that leverage AI/ML for process optimization, predictive modeling, and data-driven decision-making in chemical systems. We seek
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multimeric complex prediction. You have experience of microbiome sequencing, genome mining, or metagenomic data analysis. You have worked with host-pathogen interaction models, antimicrobial peptides
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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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estimation of engineered tissue properties developing prediction models of engineered cartilage properties as a function of the mechanical loading regime. The main duty of the Doctoral Researcher (PhD Student
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. We use advanced computational technologies to discover how biomolecules and organisms function and interact. We pioneer new methods for prediction, prevention, diagnostics and treatment of diseases. In
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understood. Most current assessments are based on inflow–outflow measurements, providing limited insight into what happens inside the systems and leading to substantial uncertainty in design, modelling, and
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, effort, and experimental expenses, and to provide data that is unachievable through experiments. Chemical kinetic models form the basis for a predictive tool, used to understand, optimise, and engineer