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equations, numerical analysis, mathematicalmodels in biomedicine, biostatistics, machine learning, statistical learning, multivariate statistics, time series,mathematical modelling, generalized linear models
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application d) Previous experience with computational modelling and machine learning. Additional optional skills and qualifications: Experience with Soft and Living Matter. Contracting requirements
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models for the fire resistance of LSF walls, including the development of machine learning models, experimental testing, and numerical simulations, within the project “FireLSF – Development of Predictive
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Using Machine Learning Algorithms (Plasmon-2Detect), ref. COMPETE2030-FEDER-00714300, number of the project - 16004, financed by the European Regional Development Fund (ERDF), with a view to the