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. Key responsibilities will include but are not limited to: Design and execute thermomechanical characterization of polymeric/composite systems Develop techniques to fabricate model fiber/composite
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Do you have a strong technical background in Machine Learning and Numerical Modelling? Are you interested in working with industry to develop Machine Learning methodologies and protocols needed
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of group's research is focused on source apportionment of size-resolved AA based on mass concentration data, chemical composition and particle number size distribution. The application of receptor models using
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model and biological membranes. The experimental data will be paired with results from molecular dynamics simulations to provide a complete characterization of the biophysical properties of the imaged
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stabilising structures iv. AI-enabled structural analysis, optimisation and design tools for high-efficiency, low-carbon composite building systems Plan and conduct experimental work, including but not limited
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capabilities in modelling of thermal compositional multiphase flow and coupled process-structure interaction in fractured porous media. Qualifications and personal qualities Applicants must hold a Norwegian PhD
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Centre for Population Research, School of the Environment. The role will support the development of a new population projection model to examine the short and long-term impacts of migration policy
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) - Strong quantitative/data skills (e.g., Matlab/Python/Origin/JMP) for processing large datasets, fitting models, and producing publication-quality figures. - Track record of technical writing (peer-reviewed
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related to ammonia-based energy systems under the School of Mechanical and Aerospace Engineering. The roles of this position include: Develop and validate thermodynamic and process simulation models
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Biotechnology and Bioprocesses, Membrane Technology, Chemicals and Materials, Resource Recovery, and Modeling & Artificial Intelligence. By harnessing its cross-cutting, interdisciplinary, and transformative