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, master's or Ph.D. in Electrical and Computer Engineering, Computer Science or related field. Solid understanding of wireless communications and networking, including 5G systems, open RAN, and network slicing
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, master's or Ph.D. in Electrical and Computer Engineering, Computer Science or related field. Solid understanding of wireless communications and networking, including 5G systems, open RAN, and network slicing
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that machine learning applications are developed with ethical considerations in mind. Participate in regular meetings with the research group. Required Qualifications* Ph.D. in Electrical Engineering, Computer
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focus of this Winanga-y Postdoctoral Fellowship role is to address a critical gap in agricultural technology adoption by investigating how AI and machine learning outputs can be better translated
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the world. Each of the four campuses (two in Chicago, one in London, and one in Hong Kong) reflects the architectural traditions of its environs while offering a state-of-the-art learning environment. Chicago
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to the project’s scope, such as mechanistic interpretability of LLMs, robustness verification of machine learning models, and conformal inference. Applicants should demonstrate scientific creativity, research
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machine learning methods to the analysis of large-scale astronomical datasets, with a particular emphasis on time-domain astronomy. Research directions will be flexible and shaped according to mutual
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The University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 3 months ago
, and safety profiles, and how these relationships can be predicted using machine learning based on drug-specific information, patient demographics, and clinical trial data. 2. Modeling for Regulatory
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cause. We are also interested in genetic interactions (epistasis), tandem repeats, machine learning, and other areas of AD research that have not yet been explored extensively. You will be part of a
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implementing bioinformatics pipelines from raw data, applying a range of advanced statistical, machine learning, and artificial intelligence (AI) techniques to analyse 'omics and clinical data, and contributing