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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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erosion and sedimentation processes, aiming to compare results with existing stratigraphic data and drainage evolution models. * Quantitatively assess data uncertainties and result errors throughout
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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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from electricity generation for charging EVs, buses, trucks, rail, pavement resurfacing, tire and brake wear, and supply chain effects. Conducting life-cycle uncertainty assessments of building materials
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uncertainty analysis of Earth Observation data products, supporting their informative uses for various applications through next-generation geospatial tools. Your qualities We seek a highly motivated candidate
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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
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Postdoctoral Researcher in Machine Learning of Isomerization in Porous Molecular Framework Materials
Experience in uncertainty quantification or statistics applied to quantum chemistry and machine learning would be advantageous For more details, please take a look at the role profile. We'll still consider
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University, and is expected to start in early July 2025. The candidate will be responsible for the following, but not limited to: Conducting research on uncertainty quantification for thermospheric density
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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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a testbed of micromorphic numerical models, and metamaterials. Proposing experimental methods to obtain micromorphic models under small and large strain, with coupled uncertainty quantification