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at the intersection of AI, RF, and wireless communication. Your main tasks include developing machine-learning methods for wireless interference detection, mitigation, edge intelligence, and applying AI to optimize RF
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to develop and implement machine learning/deep learning tools for personalized medicine in cancer by exploiting electronic medical records and medical images in relation to cancer diagnosis and the
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tools, and secure data pipelines to advance pediatric healthcare. We work at the intersection of clinical medicine, machine learning, and data-intensive research, collaborating closely with hospitals
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citation record must be focused on AI; or alternatively (B), machine learning engineers with an AI-focused PhD and demonstrated 2-year industry experience in AI development Applicants must have in-depth
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: This project is related to machine learning for Urban Informatics. In this context, the intersection between the urban infrastructure and digital technologies plays an essential role. The aim is to develop
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Computational complexity in adiabatic quantum computation AI to boost quantum technologies (e.g., machine learning for quantum error prevention/mitigation/correction) Quantum machine learning Quantum cloud
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Swiss Federal Institute for Forest, Snow and Landscape Research WSL | Switzerland | about 1 month ago
seek candidates with strong skills in programming (e.g. R or Python), statistics, machine learning, and data science. A good publication record with respect to your career stage and research interests in
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-France 75 005, France [map ] Subject Areas: Machine Learning Statistical Physics Appl Deadline: 2026/01/15 11:59PM (posted 2025/11/04, listed until 2026/05/04) Position Description: Apply Position
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 13 hours ago
Lab at UNC-Chapel Hill is seeking a highly motivated Postdoctoral Research Fellow to join our group at the intersection of statistical methodology, machine learning, and biomedical data science. Our
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will have the opportunity to engage with NYU FAS deans, faculty, and postdocs to: Learn best practices to prepare for the faculty recruitment, application, interview, and selection process; Write