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predictive models of immune responses. Develop advanced and innovative machine learning methodologies and analyze data. The postdoctoral researcher will join the groups of T. Mora and A. Walczak, whose
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, to eventually capture them in physical-chemical models that predict the impact of acidification on marine P cycling. The PHOSFLUX project is a collaboration between the NIOZ (dr. Peter Kraal) and Utrecht
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large-scale genomic, phenotypic, environmental, and field trial datasets, you will benchmark AI and quantitative genetics methods, develop multimodal and hybrid modelling frameworks, and investigate
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, predictive modeling, machine learning, and causal inference methods. Experience with claims-based or EHR-based phenotyping, variable construction, treatment pattern analyses, healthcare utilization studies
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, observations, a hierarchy of numerical models, and machine-learning methods to understand their formation, dynamics, and predictability. The successful candidate will have substantial freedom to develop
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-truth data collection, and operating, testing, validating, and refining crop models to improve prediction accuracy. The candidate will also contribute to the development and application of machine
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-particle physics, predictive modeling, and AI-enabled digital twins for magnetically confined fusion plasmas in tokamaks. The research will combine high-fidelity simulations, reduced transport modeling
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modelling, combining ecological theory with modern, reproducible approaches to understand and predict biodiversity change. Based in Potsdam, Germany, immediately southwest of Berlin, the position offers
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. Research activities may include common- and rare-variant association studies, survival and longitudinal analysis, multi-state disease modeling, polygenic risk prediction, gene-environment interaction, cross
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learning for cardiovascular digital twins and AI-enabled precision treatment. The postholder will develop patient-specific models that integrate multimodal clinical, physiological, imaging and sensor data