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Field
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learning models to predict ion-exchange isotherm parametersIntegration of predicted parameters into the CADET chromatography simulation framework Simulation and analysis of batch and gradient elution
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heavily relies on empirical determination of key model parameters. By combining protein structure descriptors, molecular simulations, and machine learning, this PhD project seeks to predict ion-exchange
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Your Job: At the Institute for Advanced Simulation – Data Analytics and Machine Learning (IAS-8) we are looking for a PhD student in machine learning to work within a project linked to the
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an impact in a societally relevant application In your application, please include a statement of research interest, CV, copies of exams, degrees and grades (transcript of records), a copy of your Master
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 7 hours ago
is also leading the development and validation of novel machine learning methods for LEGEND simulations and analysis. We have been heavily involved in constructing, commissioning, and operating
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for a highly motivated PhD candidate to join our world-leading research program in Earth System modelling and improving Earth System Modeling by better merging of measurement data and model simulations
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numerical simulations to reproduce and predict magnetically confined fusion plasma experiments 2.Development of transport models based on simulation data and their implementation into integrated transport
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the use of large language models to support neural network design and data preprocessing. The position involves close collaboration with experts in cardiovascular simulation and Scientific Machine Learning
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the behavior of complex rotating machinery operating under extreme conditions. Through the integration of modeling, simulation, and experimental validation, the group supports the design, performance
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the project SOMIPs - Simulation, Optimization and Monitoring using AI-based Digital Twin Technology for Incineration Plants The call is governed by this Notice of Opening, the University of Coimbra Research