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digital twins that simulate and predict nitrogen use efficiency (NUE) in forage grasses and oats. By combining high-resolution phenotyping data from the TraitFinder system, drones, and robotic sensors with
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of Oslo. via Unsplash Main responsibilities The position is fully embedded (100%) within SmartForest. The main responsibilities include: Developing supervised deep learning algorithms for 3D laser data
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democracy design experiment: Making the UK exam algorithm controversy game. Design Studies, 91, 101245. Hicks, B., Kitto, K., Payne, L., & Buckingham Shum, S. (2022). Thinking with causal models: A visual
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algorithm controversy game. Design Studies, 91, 101245. Hicks, B., Kitto, K., Payne, L., & Buckingham Shum, S. (2022). Thinking with causal models: A visual formalism for collaboratively crafting assumptions
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. N., Benn, C., Kitto, K., Knight, S., & Zhang, V. (2024). A technical democracy design experiment: Making the UK exam algorithm controversy game. Design Studies, 91, 101245. Hicks, B., Kitto, K., Payne
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/Machine Learning (AI-ML) approaches to meeting this challenge. Possible topics include, but are not limited to: storylines for plausible narratives of regional climate change, novel algorithms for rare
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for plausible narratives of regional climate change, novel algorithms for rare event sampling or ensemble boosting, and the development and use of hybrid climate models combining physics-based and ML components
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for plausible narratives of regional climate change, novel algorithms for rare event sampling or ensemble boosting, and the development and use of hybrid climate models combining physics-based and ML components