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public health. In this role, you will develop and evaluate novel AI and machine learning methods using large-scale multimodal datasets, contributing to epidemiology-informed foundation models, predictive
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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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explainable AI strategies to improve prediction, interpretability, and breeding decision-making. Join TEAM-AI to translate cutting-edge analytics into practical solutions for global food security. TEAM-AI aims
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Affairs. The FY27 minimum is $79, 056. Our research team is seeking a postdoctoral scholar interested in cardiovascular and cardiac surgery outcomes research and predictive analytics using advanced
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molecular representations, off-target prediction, and experimental feedback. The developed methods will be applied in iterative prospective drug-discovery cycles, with a serine protease from the complement
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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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properties predicted by Virtual-Coater™ can be translated into meaningful input parameters for battery modelling platforms. The ultimate objective is to establish a predictive modelling workflow capable
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and apply AI and machine learning methods for signal processing, image analysis, data fusion, and prediction; · build physics-informed and hybrid AI models that combine geophysical knowledge with data
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in the ongoing project ProcTwin that investigates how a distributed AI system can capture and predict the behavior of a production system under operational conditions. The project develops data
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) infrastructure of New York State’s Empire AI enabling us to train large AI models that will outperform traditional numerical prediction models. Duties: ● Design, train, and evaluate novel AI/ML models. Develop