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for probabilistic unsupervised learning for structured biological data. The successful candidate will: Develop probabilistic factor models and scalable inference algorithms for structured biological (multi-view) high
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who works at the intersection of numerical methods, scientific computing, and data-driven modeling. The position is devoted to the development, analysis, and implementation of flexible, tailored, and
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Instituto de Ciência e Inovação em Engenharia Mecânica e Engenharia Industrial | Portugal | 3 months ago
of numerical simulation, computational modeling, optimization, or digital twins Experience in simulation-based optimization, including Bayesian optimization, derivative-free optimization, model calibration
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properties of primordial black holes (PBHs) and exotic compact objects in the context of beyond the Standard Model (BSM) field theories. Specifically, the research will focus on: • study of PBH formation
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of numerical models to study acoustic and optical interactions in metasurfaces, using in-house codes and COMSOL Multiphysics software. 2. Geometry and Material Optimization: Systematic exploration of structural
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/or projects with preference to those involving modeling utility systems. Demonstrated project work / capabilities in numerical modeling, data analysis with background in quantitative hydraulic
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the research line “Modelling, numerical simulation, optimization and control of scientific and industrial problems”. JOB VACANCY REFERENCE: CITMAga-OT-09/2026. DESCRIPTION OF JOB POSITION: 1 full-time as an
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analysis, and/or numerical modeling. Experience in modeling and evaluating the impacts of climate and climate change, large-scale data analysis and interpretation, and independent research is required. City
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of metamaterial-based supports in attenuating vibrations of the single beam/coupled beam/metabeam systems. • Development of the mathematical models of the single beam/coupled beam/metabeam systems under
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experimental characterization, numerical simulation, data-driven approaches and artificial intelligence tools. The successful candidate will contribute to the development of a digital environment capable of