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Physics based machine learning algorithm to assess the onset of amplitude modulation in wind turbine noise (with TNEI Group) EPSRC Centre for Doctoral Training in Sustainable Sound Futures PhD
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Job Description DTU Electro invites applications for a PhD position in digital signal processing and machine-learning-enabled continuous-variable quantum key distribution (CV-QKD). The position is
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for machine learning, with research topics ranging from decentralized and federated optimization, adaptive stochastic algorithms, and generalization in deep learning, to robustness, privacy, and security
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possess knowledge and skills in computer science, particularly in the areas of algorithms and data structures, databases, distributed databases, data warehousing and analytical processing, knowledge
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will contribute to areas such as the design and analysis of algorithms (e.g. randomized, quantum, approximation, property testing, online, streaming, sublinear, fine-grained, distributed/parallel) and/or
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Job Reference: 1168098 About the Role: You will play a key role in advancing distributed and adaptive AI methods, focusing on scalable software frameworks, learning algorithms, and orchestration
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and Prisma stack. Help integrate the application with the Jutge.org public API to synchronize data. Collaborate in the implementation of algorithms for the automatic evaluation of the difficulty
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About the Opportunity The Postdoctoral Research Associate advances research in mathematical modeling, optimization, and stochastic analysis for large-scale and distributed systems. The role focuses
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The University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 22 days ago
, and medicine. Key Responsibilities Collaborate with researchers to design, develop, and refine large language and generative models. Develop novel algorithms for generative modeling tasks and optimize
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conditions are caused, transmitted, and prevented, as well as how they are distributed throughout the population. Such information plays a critical role in guiding policies and other evidence-based strategies