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engineering or physics of electronic or optoelectronic devices is required Prior experience in numerical simulations, applied mathematics and/or machine learning is an advantage Interest and enthusiasm in
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evaluate them alongside newly developed approaches. Integrating methods such as case weighting, anomaly detection, and model-based prediction (e.g., geostatistics and machine learning), using auxiliary
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methodological and interdisciplinary research, and willingness to learn from different fields, including transportation, human-computer interaction, and urban planning. Good communication and writing skills in
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strengthen the data science and machine learning activities of the IAS-9 with exciting new topics. You will work in a multidisciplinary team of enthusiastic data scientists, software developers and domain
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filled The overarching aim of this project is to find synergies between methods and ideas of modern machine learning and of statistical mechanics for the study of stochastic dynamics with application
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that combine principled reasoning with the efficiency of modern machine learning to enable intelligent, real-time decision-making in large-scale interconnected systems. This position offers the opportunity
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Computational Fluid Dynamics (CFD) models; data-based models determined from training/calibration data by system/parameter identification and machine learning. The key challenge is striking a balance between, on
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synergies between methods and ideas of modern machine learning and of statistical mechanics for the study of stochastic dynamics with application to the analysis of time series. In particular, the project
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-based control and decision-making for complex multi-agent systems. The project explores new computational frameworks that combine principled reasoning with the efficiency of modern machine learning
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analyses and machine learning. Some data for the project already exist, but additional data will be collected from behavioural tests on privately owned pet dogs in Sweden and abroad (Europe). Travel and time