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. The research will focus on artificial intelligence, machine learning, data analytics, and recommendation systems, with applications to personalized decision-making, digital platforms, digital health, and mental
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University of North Carolina at Charlotte | Charlotte, North Carolina | United States | about 22 hours ago
: ‘Omics of Cnidarian Immunity Duties and Responsibilities A Postdoctoral Fellow (""postdoc"") is a professional apprenticeship designed to provide recent Ph.D. recipients with an opportunity to develop
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diagnostics and therapeutic stratification in lung cancer. In collaborating with cross-functional teams, including bioinformatician, computer scientists, AI engineers, biologists, and clinicians, you will
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research in various areas of mobile network systems, multimedia and AR/VR/XR systems, robotics and machine learning, focusing on fundamental aspects as well as on applications in multidisciplinary contexts
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-dimensional statistics, machine learning theory, or more broadly, mathematical foundations of AI. The appointment will be for up to two years with annual renewal based on satisfactory performance and continued
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opportunity to learn from our highly interdisciplinary, collaborative, and dynamic research group that meets regularly and includes leading scientists (and other fellows) with expertise in several disciplines
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sustainable manner. Key Responsibilities: Responsible for developing explainable machine learning algorithms for Tunnel Boring Machine (TBM) tunnelling and excavation Developing large language model enhanced
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computing environments and GPU computing. Proven experience in weather and climate models development and applications. Experience in machine learning, deep learning, or AI applications for atmospheric
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at King’s are entitled to at least 10 days per year (pro-rata) for professional development. This entitlement, from the Concordat to Support the Career Development of Researchers , applies to Postdocs
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predictive deep learning models, and physical mechanistic models (thermodynamic and kinetic models etc.). Examples of suitable backgrounds: machine learning, programming, mathematics, physics. You will