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materials, including porous dimension, building ingredients, wettability, etc., and their interactions with water and gas species include CO2, Hydrogen and methane. Using atomistic modeling, the study will
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the Translational Research Accelerator (TRA) theme that will contribute to model development and establishment, to address clinical questions raised within the three projects. The PhD project will be within TRA, and
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are only recently recognised as potential threats, and Arctic-relevant ecotoxicological data remain extremely scarce. Current regulatory risk assessments rely on temperate model species and single-compound
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of how casting-induced defects and microstructural heterogeneities influence fracture behavior, and to develop improved modelling approaches for predicting failure in these materials. Duties
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? We urgently need breakthrough research in: recyclable & durable materials fast, data-driven surrogate models lifecycle-conscious design to reduce costs, increase reliability, and accelerate the North
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candidate with a background in aquatic sciences, environmental chemistry, biogeochemistry, or a closely related field, with experience in field measurements, modelling, or both. Special emphasis
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SFI FAST: PhD position in Microstructure/texture evolution during extrusion of scrap-based Aluminium
physics- and data-driven models that deal with microstructure/texture evolution during extrusion to predict material properties of extruded profiles Collaborate with other researchers and industry partners
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for Materials Science and Nanotechnology. The successful candidate will play a key role in establishing an experimental research line within Associate Professor Ainara Nova’s research group in the Section
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of Science and Technology (NTNU) for general criteria for the position. Preferred selection criteria Knowledge of constitutive modelling of materials. Knowledge of non-linear finite element methods. Knowledge
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and Technology (NTNU) for general criteria for the position. Preferred selection criteria Knowledge of plasticity theory. Knowledge of constitutive modelling of materials. Knowledge of non-linear finite