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logistics. In this context, numerical simulation plays a central role for prediction, design, and decision support. In modern applications, models are frequently multi-physics, involve strong couplings across
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/acoustic sensors) Analysis of hydrodynamic processes, turbulence structures, and sediment transport mechanisms governing scour evolution Simulation of high-fidelity CFD simulations for modeling wave
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AMMETIS[1] (AI-assisted Simulations of Microstructure driven MEchanical properties from high Throughput and multiscale analysIS), in the framework of PEPR DIADEM[2] , which aims to develop an advanced
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Fundación para la Investigación Biomédica del Hospital Gregorio Marañón (FIBHGM) | Spain | 5 days ago
or Engineering Where to apply Website https://www.iisgm.com/ofertas-de-empleo/ Requirements Research FieldOtherEducation LevelBachelor Degree or equivalent Skills/Qualifications Minimum job requirements: The
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to refine models. The results will be used to calculate radiation doses and evaluate global risk using TGF-detecting satellite catalogues and recent airborne campaign data. Where to apply Website https
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be embedded within Moderna's Clinical and Quantitative Pharmacology (CQP) function and will contribute to key modeling and simulation deliverables for drug candidates across early and late stages
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observations, atmospheric chemistry models, and physics-informed deep learning, validated through field campaigns. Key Responsibilities Conduct atmospheric chemistry simulations Develop deep learning models
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address key challenges within these processes, constructing robust models and simulations that deepen the understanding of the underlying physics involved. The ultimate goal is to create predictive, physics
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improvement. The NASA Ocean Biogeochemical model (NOBM) was developed at GSFC and is coupled with the GISS climate model. It simulates the ocean carbon cycle using phytoplankton groups differentiation. Research
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quantification of pigments and binders. The work will include the generation of simulated spectral data based on physical models, the training and optimization of machine learning models, and their validation