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deployment enabling validation and demonstration of real-world applications. For more details, please view https://www.ntu.edu.sg/erian We are looking for a Research Fellow to design and develop advanced power
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algorithms have been developed, most based on a hybrid architecture combining transform coding and predictive coding. Standards such as H.264/AVC, HEVC, and VVC follow this principle. While they offer highly
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Inria, the French national research institute for the digital sciences | Palaiseau, le de France | France | 12 days ago
scientists developing computational simulations in various fields will be encouraged, in particular with the Gysela code, which is part of the ITER project. The project will first focus on dimensionality
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Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID | Portugal | 12 days ago
be developed at VisLab of Institute for Systems and Robotics, under the scientific supervision of Prof. Catarina Barata. Website for additional job details https://ist-id.pt/concursos/bolsas/ Work
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the algorithmic capabilities of intelligent systems, reducing their computational costs, and bridging the gap between hardware and algorithm design. Duties and responsibilities The appointment as a postdoctoral
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The Quantitative Genetics research group is interested in developing statistical genomics toolboxes to decipher the genetic architecture of important crop traits, such as grain yield, adaptation
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the activities of GT3. The initial phases will focus on studying the ideal frameworks for creating the IT platform and developing AI algorithms for data analysis. In particular, the data storage structure will be
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in the Phi_Lab, led by Dr. Azeem Ahmad, and will focus on the development of advanced reconstruction algorithms and next-generation quantitative optical microscopy and tomography systems for imaging
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the development of efficient algorithms and codes for multilinear algebra, with a particular focus on the use of innovative parallel programming models and tools. In the context of this task and as part of the Exa
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, transfer learning, federated learning, data integration, algorithmic fairness, survival analysis, and methods for heterogeneous and multi-source data. Training Environment and Career Development