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of Professor Kevin Coulembier and Associate Professor Daniel Tubbenhauer . The project is concerned with representation theory in a broad sense, with a focus on the role of monoidal (tensor) structures and on
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University of Stavanger invites applicants for a PhD Fellowship in Surrogate Modelling of Fluid Flows using Deep Learning at the Faculty of Science and Technology, Department of Mechanical and Structural
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part of the research team to establish and understand the structuration of algae/soybean/mung bean proteins for high quality alternative protein foods including through high moisture extrusion. Key
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fabrication of novel knitted structures embedded with energy-harvesting yarns. You will be expected to: Apply fundamental understanding of material–structure–function relationships in knitted fabrics Overcome
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-training, post-training and reinforcement learning for Large Language Models (LLMs); (c) lead the pre-training of both Dense and MoE LLMs, optimising for performance, scalability, model structure and
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techniques for global and regional seismology. Travel time tomography, on regional and global scale, has been one of the main tools in determining the Earth’s velocity structure. Among other things, travel
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Theory (DFT) calculations using established codes (e.g., VASP, FHI-aims). Demonstrated experience with traditional methods for modeling atomic site disorder, such as special quasi-random structures (SQS
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materials, with microwave metamaterial and device designs, to help develop a new class of reconfigurable electromagnetic structures. This will involve using various simulation programmes, both for mechanical
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research that integrates engineering models of power systems with modern econometric and economic analysis. Responsibilities include conceptualizing and implementing statistical and structural models
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integrates behavioural and cognitive assessments with neuroimaging and AI, including neuropsychological testing, cognitive tasks, functional Magnetic Resonance Imaging (fMRI), structural MRI, and predictive