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Multi-modal Machine Learning-including areas like Neuro-symbolic AI, Knowledge Graphs, Contextual AI, Conversational AI, and Trustworthy & Safe AI. This role also offers the opportunity to explore human
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positions for distinguished professorship. Candidates in areas including, but not limited to, Algebra, Number Theory, Geometry, Topology, Combinatorics, Graph Theory are encouraged to apply. Responsibilities
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to capture the spatial complexity of tumor organization and its relationship to treatment response. This PhD project aims to develop robust multimodal predictive models of platinum resistance using a large
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. A particular focus of the project will be on: 1) Graph Neural Networks for cosmology, neutrino and/or collider physics, 2) Domain adaptation methods / model robustness, 3) Uncertainty quantification
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medicine at the University of Chicago. Chun-Su Yuan, MD, PhD, Director of the Center, follows the philosophy: The most important thing is to make discoveries to benefit our patients. Thus, researchers in
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management, anomaly detection, etc.) is considered a significant asset. Similarly, integration and exploitation of knowledge (ontologies, knowledge graphs, formal models, neuro-symbolic approaches, expert
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learning, physics-informed neural networks, graph neural networks, transformers, convolutional defiltering methods, etc.) for the integration in multi-physics simulation codes You will develop code for and
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Environmental science » Other Researcher Profile First Stage Researcher (R1) Positions PhD Positions Application Deadline 8 Feb 2026 - 23:59 (Europe/Paris) Country Belgium Type of Contract Temporary Job Status
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collected or results of experiments, tests, surveys, programming, etc, or provide data for use in other manuscripts or reports. May produce charts and graphs to display trends in data. Performs routine
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analyses. · Generate tabulations and visual representations of data (e.g., charts, graphs) using report-building tools with minimal oversight. · Interpret analysis results and contribute