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anomalies in evolving graphs. In this research proposal, our aim is to explore the parallels of deep learning and anomaly detection in dynamic graphs. In particular we are interested to redesign deep neural
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Project Description The next generation of signal processing, computing and artificial intelligence (AI) technologies will be unlocked by the close integration of electronics and photonics
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will encourage their implementation, especially by using parallel computing. * Assigned department Existing departments [Work location] * Address 606-8501 Kyoto Minato Laboratory, Graduate School
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Python and C/C++. Expertise in ensemble learning (e.g., Random Forests, Gradient Boosting, bagging/stacking frameworks). Hands-on experience with parallel or GPU-based computing (CUDA, OpenCL
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Job Status Full-time Offer Starting Date 2 Nov 2026 Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research
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) Zhongtian Sun (School of Computing, University of Kent) Aligned programme of study: PhD in Network Science Northeastern University London As part of a major investment, Northeastern University London (NU
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Posting Description SENIOR ARCHITECT AND TECHNICAL LEAD - OPEN PORTABLE INTEGRATIONS FOR AGENTIC RESEARCH COMPUTING, MA Green High Performance Computing Ctr, to serve as the technical lead and
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the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Le trouble du stress post-traumatique (TSPT
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-based systems to large-scale GPU systems, enabling users to effectively leverage next-generation architectures. Initiate and conduct research into new high performance and parallel computing applications
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Engineering Computer science Researcher Profile First Stage Researcher (R1) Application Deadline 30 Apr 2026 - 21:59 (UTC) Country Sweden Type of Contract Not Applicable Job Status Full-time Is the job funded