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Prof. Neil Walton (Durham University, UK). The general aim of this project is to develop throughput-optimal entanglement distribution algorithms (both centralized and decentralized algorithms
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(ISAC). Responsibilities: Lead the design, setup, and execution of ISAC channel measurement campaigns across multiple environments, hardware platforms, and frequency bands Develop, validate, and document
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: image processing, machine learning, and patient records. Track record of development and implementation of novel machine learning algorithms in the healthcare setting or other spaces. Extensive experience
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-transparent materials, and the utilisation of deep learning algorithms to accelerate computational solutions. Scientific Objectives Develop a self-contained finite volume solver for solidification of multiphase
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strategies (e.g., feature attribution, counterfactual explanations, dialogue-based explanations, hybrid symbolic–ML approaches); develop user-facing explanation interfaces that connect algorithmic reasoning
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la stabilité des algorithmes et à l'efficacité computationnelle. Une partie de la thèse sera également consacrée à des travaux expérimentaux visant à caractériser le comportement mécanique de systèmes
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of dynamic outdoor thermal comfort. This objective aims to reduce the computational demands of microclimate simulations and thermal comfort analyses by developing fast parametric algorithms and data-driven
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such as scalable identification algorithms, uncertainty quantification, and the integration of learning-based models with formal verification. We offer a supportive, inclusive, and collaborative research
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to be developed: Analyze iEEG data. Develop multimodal algorithms. Perform the characterization of the epileptogenic network. Where to apply Website https://seuelectronica.upc.edu/en/procedures/call-for
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Designated Countries will not be accepted at this time, unless they are Legal Permanent Residents of the United States. A complete list of Designated Countries can be found at: https://www.nasa.gov/oiir/export