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-scale human datasets. You will: - Build and apply machine learning and deep learning models to multi-scale (cells, brains, patients), multi-modal (omics, biosensor data, vision, electronic health data
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of generative AI tools, use of large language models, machine learning, and ethical frameworks for AI implementation. Ability to apply AI to interdisciplinary research or developing AI models
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, machine learning, governance and operations, we aim to address the complex challenges and opportunities of space exploration CfAI is a large research group in the Department of Physics at Durham University
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Previous Job Job Title Postdoctoral Associate in Mathematical Foundations of Generative AI Next Job Apply for Job Job ID 375806 Location Twin Cities Job Family Academic Full/Part Time Full-Time
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associate will be conducting research on topics in machine learning and computational materials science.. In compliance with NYC’s Pay Transparency Act, the annual base salary range for this position is
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machine learning approaches to build a system that highlights promising locations for archaeological research. You are also expected to play an active role in project coordination and in writing follow-up
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through data-driven modeling and optimization. The successful candidate will work at the intersection of thermal-fluid sciences, control theory, and artificial intelligence/machine learning to advance
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to have published in leading machine learning conferences or similar venues. One or two PDRAs will be recruited to work within one of, or across, the four research themes: Learning with Structured
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to the development of remote sensing algorithms, simulation and modeling capabilities, and artificial intelligence/machine learning (AI/ML) methods in support of the goals of the joint NASA/USGS Landsat mission
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Postdoctoral Research Associate position. The successful candidate will hold a Ph.D. in marine biology or a closely related field and will have experience in marine geospatial analytics, remote sensing, machine