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Field
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and colleagues working with theory that will complement your work with density functional theory, phase-field simulations, and finite element modelling. Qualified applicants must have: Enthusiasm
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the previous point and the documents proving the conditions in this Notice, namely: a) Application for Application addressed to the President of the Selection Jury (model attached); b) Copy of doctoral
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science, computer science, applied mathematics or a related field a strong background in machine learning, material modeling, and metals processing, modeling and simulation (This will be a clear advantage
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the terms defined in the attached model. 16.4. The application is accompanied by the documents proving the conditions in this Notice, namely: Request required in point 16.3, above; Copy of doctorate
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to facilitate a rapid and efficient exchange among experimental and computational groups and Devise an approach in invertible predictive modelling that links semiconductor properties to the composition of lead
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industrial processes. Your research will drive a paradigm shift in how TES systems are modelled, integrated, and controlled within industrial settings. You will develop novel, adaptive, physics-informed models
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its stability and power quality compliance in relevant operating conditions. The Researcher will be employed at the Norwegian University of Science and Technology (NTNU) and the workplace will be in
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models that integrate data from quantum simulations and experiments, using techniques such as equivariant graph neural networks with tensor embeddings. We aim to train these methods in a closed-loop
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-pathogen interactions using in vitro model systems mimicking chronic diseases. The project foresees ample collaborative opportunities with research groups in the MICRO-PATH consortium, spanning
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an extrusion machine that produces large-scale earth blocks Building a 3D printer that utilizes earth materials for construction purposes Developing numerical process models that simulate 3D earth printing