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, engineering, computational science or relevant field(s). Experience in developing numerical code, preferably fortran, is required. Preference will be given to candidates with experience in modeling edge and
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using FRF and FDD models. Execution of fatigue tests on various materials. Numerical, analytical, and experimental analysis of mechanical components under fatigue regimes, additive manufacturing (AM
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postdoctoral researcher to join the ERC Pandora project team. Your work will involve analyzing or designing models of surface processes to estimate their role in the formation of environmental refuge zones
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skills to model and design optical systems for sustainable high-tech devices for billions of people? Do you like to develop and analyze numerical methods for partial differential equations? Information
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 1 hour ago
, as articulated in the School’s Strategic Plan (https://pharmacy.unc.edu/about/oe/strategic-plan/). Our Vision is to be the global leader in pharmacy and pharmaceutical sciences. Our Mission is to
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collection • Skill and interest in data modeling using physically-based numerical and statistical tools Language skills • Fluency in English, both oral and written. Skills in French is an asset. Your LIST
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controllers, and PID controls), and preferred sensors (LiDAR and RADAR) is required. Excellent oral and written communication skills. Preferred Qualifications: Familiarity with state-of-the-art models for AI
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tissues - development of numerical simulations of gastrointestinal motility - temperature-dependent optical mapping data analysis Where to apply Website https://www.unicampus.it/concorso/contratto-di
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computational modelling the primary tool for their safety analysis. The challenge is to develop a methodology that is both scientifically rigorous and practical for safety and licensing efforts. Current transient
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of freedom per dimension d. Foundational kinetic models often have N∼256 and d≥6, making direct numerical simulation intractable with traditional approaches. Through innovative work combining machine learning