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Field
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processing parameters, including precursor composition, temperature, mixing conditions and reaction time, on material purity, particle morphology and performance. Characterising precursor, intermediate and
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focus in probability theory or a closely related area. Strong research record Preferred but not required: Research experience in KPZ, interacting particle systems, integrable probability, first or last
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for recruitment positions and for general criteria for the position. Preferred selection criteria Knowledge of in Norwegian/Scandinavian language Experience with GPU based systems Experience with HPC based
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quantify carbon sequestration capacity. • Investigating the influence of particle size, moisture content, curing conditions, and material composition on carbonation efficiency and long-term carbon storage
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experience with probabilistic or computational modelling. Experience with language model evaluation, cognitive modelling, reinforcement learning, goal-directed behaviour, learning theory or large-scale GPU
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to formulation science, such as HPLC data analysis, spectroscopy, or particle sizing software. Experience of designing, developing or refining experimental methodologies to generate reliable and reproducible data
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to: Contribute to development and deployment of particle imaging systems for use in breaking waves, both in the field and in the lab Contribute to analysis of images, and development of the open-source analysis
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, working closely with other project participants on field measurements, laboratory work and model development. The candidate will be expected to: Contribute to development and deployment of particle imaging
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, research or support services. Researchers and students at the Faculty of Science are fascinated by every aspect of how the world works, be it elementary particles, the birth of the universe
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parallel programming and/or high-performance computing, particularly on GPU or FPGA architectures; Knowledge of compression techniques, including predictive coding, filter banks, transforms, and statistical