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of many-body physics problems in digital quantum computers. Hybrid quantum-classical algorithms for quantum simulation and testing on real hardware. Quantum-computing enhanced sensing. Mandatory
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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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of Computer Science and Electrical and Computer Engineering. INESC-ID’s research impact is focused on four Thematic Lines Energy transition Life and health technology Security and privacy Societal digital
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) demonstration of oral and written language proficiency in English (with reference to the context where the candidate learned and perfected the language use); b) Detailed Curriculum Vitae; c) Copies of PhD degree