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Field
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or more of the following areas: Advanced Process Control and Optimization Digital Twin and Modeling & Simulation Predictive Maintenance and Fault Diagnosis Industrial IoT and Edge Computing Good programming
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developed using finite element analysis (FEA) between LMGC, ICube and LEM3 Labs to model the behaviour of Wharton's jelly samples in an ex vivo and in vivo context. Predictive tools, based on previous models
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Intelligent Control Systems RESPONSIBILITIES Develop industrial process digital twin models based on the fusion of mechanistic and data-driven approaches. Develop predictive maintenance and fault diagnosis
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machine learning—for chemical and biological applications. You will design and implement models ranging from molecular to process scales, develop model-predictive control and optimization strategies, run
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The COVID-19 pandemic, caused by SARS-CoV-2, underscored the threat of (re-)emerging viruses and the need for better pandemic preparedness. Predicting the next pandemic is difficult due to the many
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Control Section is to perform research and train next-generation students on the topic of understanding and predicting the dynamics of complex engineering systems in order to develop advanced control
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, to test their potential for exploiting temperature gradients for producing electricity and predict their long-term performance under real operating conditions. The project also includes modeling of heat
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performance, and preventing failures like fires or explosions. Current prediction methods mainly rely on extensive lab testing and modeling, using insights from destructive post-mortem analyses to improve
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spatial and temporal scales, leveraging cutting-edge hierarchical Bayesian modeling approaches. The Fredston Lab uses large datasets, theoretical models, and a range of statistical tools to predict marine
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by the CNRS, the postdoctoral researcher will be responsible for contributing to the development of advanced methodologies for predicting crystal structures (CSP) based solely on their chemical