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machine learning challenges: how to learn from limited and heterogeneous data, how to combine data with physics-based models, how to solve inverse problems under uncertainty, and how to build models
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of the century, which could be further amplified by a slowdown in the Atlantic Meridional Overturning Circulation (AMOC). This PhD is part of the French-Brazilian project AMACLIM (https://www.lsce.ipsl.fr/anr
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becoming increasingly important as the energy system faces more uncertainty from weather, renewable generation, market developments, and future electricity demand. These decisions depend on uncertain inflows
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global guarantees of stability and robustness to disturbances, uncertainties and actuation limits (saturation); b) the analysis of the stability and performance properties of the proposed solutions; c
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be used to combine these datasets while accounting for their different spatial scales, uncertainties and sampling frequencies. Machine-learning methods may also be explored for retrieval, bias
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demonstrated ion trapping of single Yb+ ions. Optical clocks based on ultra-narrow transitions in trapped ions and neutral atoms have reached fractional uncertainties in the low 10-18 range, enabling landmark
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approaches. The research will focus on fundamental thermomechanical and thermofluid phenomena relevant to fusion devices and components. In particular, it will investigate uncertainties arising from
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Projection heads and harmonised embedding schema v1.0 with uncertainty application programming interface and integration guide. Deliverable: D5.2 Query Retrieval Fusion backbone v1.0 with interface
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reaction. The resulting ions enable depth-resolved quantification of Li and other components of the anode, e.g. Si, O, F, C, etc. This information provides valuable insights into the quality and stability
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—including structured households’ surveys and Agent-Based Modeling (ABM)—for the quantification of adaptation effectiveness and limits. The overall outcomes of the ADELE project will contribute to the ongoing