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expertise in neuroscience, artificial intelligence, and cognitive psychology to develop a unified theory of auditory-scene analysis in brains and machines. Close collaboration with Prof Elia Formisano's group
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are passionate about any or all of the following: Data Science, Computational Social Science, Behavioral Economics, Human-Bot interaction, Experimental Research, Game Theory, and Artificial Intelligence. Some of
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foundation model pipelines Resilience of AI systems Scaling and systems theoretic modeling of generative AI We seek applicants who are eager to push the boundaries of data science, artificial intelligence, and
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. You will incorporate field survey data, remote sensing and other auxiliary data into spatial modelling processes using techniques such as species distribution modelling and artificial intelligence
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the central hypothesis of these infections causing general stress responses and behavioural changes, which can be assessed on metabolic level or by video observation and artificial intelligence analysis
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ensembles at high enough resolution and with enough members to adequately sample internal variability and capture rare events is a challenge. This project aims to explore data-driven Artificial Intelligence
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systems spanning from novel physical layer waveforms designs (e.g., MIMO, OTFS) to artificial intelligence-enabled networking protocols; from reflecting intelligent surfaces (RIS)/integrated sensing and
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Post-doctoral Position in AI Causal models for Synchrotron Anomaly Detection H/F This post-doctoral position is part of a collaboration between LIAD (Laboratory of Artificial Intelligence and Data
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challenge. This project aims to explore data-driven Artificial Intelligence/Machine Learning (AI-ML) approaches to meeting this challenge. Possible topics include, but are not limited to: storylines
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the area of Machine Learning for Engineering Design under the guidance of Prof. Mark Fuge, the Chair of Artificial Intelligence in Engineering Design. The general area of the laboratory covers the study of