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is where science and art meet technology and business. We shape a sustainable future by sparking the game changers of tomorrow and by creating novel solutions to major global challenges. Our community
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Postdoctoral Researcher in ML for Dynamical Systems Representation, Prediction, and State-estimation
cutting edge machine learning techniques for sequential data modelling, including Physics-informed Machine Learning and Koopman Operator-based representation framework, towards building interpretable
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Postdoctoral Researcher in ML for Dynamical Systems Representation, Prediction, and State-estimation
for sequential data modelling, including Physics-informed Machine Learning and Koopman Operator-based representation framework, towards building interpretable predictive models for complex multi-physics dynamical
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on the effectiveness of mathematics interventions using randomized trials and other methodologies. Areas of focus might include mathematics assessment and discourse, examine the validity of research-based learning
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orchestra and a full schedule of seasonal events and festivals. Sports fans will enjoy Division I college athletics, Triple-A baseball affiliate the El Paso Chihuahuas and professional soccer team El Paso
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learning, focusing on fundamental aspects as well as on applications in multidisciplinary contexts. This position is part of the DRIVE project, funded by the Research Council of Norway (RCN) (2026-2030
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exciting Division I college athletics at several campus venues including Sun Bowl Stadium, where one of the oldest football bowl games takes place annually, and the Don Haskins Center arena. Southwest
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to the development, adaptation, and application of machine‑learning models tailored to RODI data (in collaboration with project partners). Designing and implementing an innovative image‑based database to manage and
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conducting quantitative analyses or master game theoretic analysis. Experience with large language models, machine learning, and/or programming in R or equivalent programs is an advantage but not a requirement
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kind of machine learning algorithm, provides more accurate data than traditional data collection methods, e.g. paper-based surveys. This data is valuable to several stakeholders: i) architects and urban