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intelligence, as it develops model learning methods based on optimization, together with predictive validation procedures designed to assess the generalization ability of models on new data. Current approaches
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learning, epigenomic data, and mechanistic modelling. The mission is to contribute to the development of predictive models of the replication initiation probability landscape (IPLS) from limited experimental
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of predictive models, multimodal data integration, development of explainable AI algorithms, analysis of clinical, biological and imaging data, and implementation of software tools supporting biomedical research
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Danfoss, you will combine thermofluid modelling, reduced-order multiphysics methods, and nonlinear rotor dynamics analysis to develop predictive modelling tools that support the industrial design of
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-based reasoning. The goal is to move beyond isolated prediction models towards an integrated agentic system that can model patient trajectories, compare treatment strategies and generate transparent
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researcher to conduct education and research related to the development of AI-based subseasonal-to-seasonal prediction models. https://www.jst.go.jp/k-program/program/kaiyou4.html [Work content and job
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-derived material, tissue engineering, microfluidics, advanced analytics, and digital technologies, NAM platforms enable the development of highly predictive and human-relevant biomedical models
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curated pharmaceutical science and public health databases that can be used for modeling purposes. Information about Dr. Zhu’s research and recent publications can be found on his lab website: https
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Sciences Location Bloomington Position Summary Position Overview The Postdoctoral Researcher will join an NSF-funded project developing and testing computational models of how decisions evolve over time. The
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will inform provincial guidelines and extension programmes, enabling scale-up beyond pilot sites. By embedding predictive modelling, antimicrobial surface strategies, and processing standardization