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Field
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experts. Good communication skills. . Nice to have experience: Statistical knowledge: Experience in uncertainty analysis, particularly in the context of large datasets and real-world statistical modelling
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• Uncertainty quantification around LLMs • Constrained optimal experimental design (active learning) • Combining models and combining data / Realistic simulation of clinical trials • Developing
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to increasing CO2 and climatic change is a large uncertainty for ecosystems, crop productivity and climate predictions. To tackle this uncertainty, we combine: growth chamber experiments, samples from world
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plants will respond to increasing CO2 and climatic change is a large uncertainty for ecosystems, crop productivity and climate predictions. To tackle this uncertainty, we combine: growth chamber
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uncertainty". The goal of this project is to advance our understanding of how humans are able to act in complex and uncertain circumstances, and how such knowledge can be applied to smooth our interaction with
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other sources to train and validate AI models. Develop computational workflows incorporating LLMs, Monte Carlo Tree Search (MCTS), phylogenetic inference, uncertainty quantification, and epidemiological
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), Proficiency with LCA software tools (e.g., openLCA, SimaPro, Brightway, Activity Browser), Experience with LCA uncertainty, sensitivity analysis, and scenario modelling, Energy systems modelling and simulation
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uncertainties and result errors throughout the whole data assimilation and modeling process. ● Other Duties as assigned. Special Notes: The Research Foundation of SUNY is a private educational corporation
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uncertainties and result errors throughout the whole data assimilation and modeling process. ● Other Duties as assigned. Special Notes: The Research Foundation of SUNY is a private educational corporation
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of biological hedging shape conservation strategies? Can financial tools like biodiversity bonds or species-indexed futures promote better ecological outcomes? How should we account for uncertainty in