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Field
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data to better understand the structure and function of the brain—across health, disease, and species. You'll work with world-class researchers in fields including network science, biophysical modelling
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coatings e.g. oxide and nitride. Drive the comprehensive characterization of thin films using advanced techniques (e.g., SEM, XRD, Raman, AFM, nanoindentation), enabling deep understanding of structure
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of nuclear structure and function. Current Opinion in Cell Biology 26, 10-18. Hazra, R., Brine, L., Garcia, L., Benz, B., Chirathivat, N., Shen, M.M., Wilkinson, J.E., Lyons, S.K., and Spector, D.L. 2022
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group selection management to promote structural complexity, making them a useful test of different modeling approaches in the Forest Vegetation Simulator (FVS). Currently FVS users, which largely consist
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. The PhD research fellow will design droplet flow experiments on fibers and focus on droplet accumulation on fibrous structures when exposed to fog flow. There will also be aspects with coupling droplet
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fellow for a research project titled, “Structural modification and update of the U.S. national harvested wood products carbon model (WOODCARB II)”. USDA Forest Service has been using the WOODCARB II model
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the last 5 years or soon to be completed. Demonstrated experience in building machine learning/deep learning models using one or more large scientific data sets involving sequence, protein structures
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either Digital Culture, Comparative Literature or Nordic Literature. The AI STORIES project is a European Research Council Advanced Grant led by Professor Jill Walker Rettberg, with a team of three
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deployment. Existing methods rely on fixed data and static models, which struggle to adapt to real-time changes and unpredictable conditions. This limits the ability to optimize energy storage use for critical
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management expert and a research assistant. AI STORIES explores the hypothesis that deep narrative structures in the datasets used to train generative AI models are replicated and perhaps exaggerated in