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to facilitate perceptual learning of different stimulation patterns; and (iii) the development of advanced AI algorithms capable of converting camera input into real-time electrical stimulation parameters. In
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of elements) of the model.; 3) develop an optimization algorithm based on genetic algorithms and metamodels and 4) design functionally graded OC scaffolds using different biomaterials. The doctoral candidate
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simulation of scenarios with different materials and geometries. - Support the development and implementation of signal and image processing algorithms, including fast inversion techniques, FFT, and nonlinear
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offer a PhD student position at the Universitat de Barcelona (as part of the PhD Program in Mathematics and Computer Science) to develop new AI and federated learning algorithms for diagnostic imaging in
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: Design, implementation and testing of new methods and algorithms so that SIESTA can harness the compute power of the latest generation of (pre-)exascale architectures and tackle novel scientific challenges
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31 Oct 2025 Job Information Organisation/Company Universitat Autònoma de Barcelona Department Research Management/Strategic Projects Research Field Computer science » Other Researcher Profile First
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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 Infrastructure? No Offer Description Introduction
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through the EU Research Framework Programme? Other EU programme Reference Number 2025-LU053 Is the Job related to staff position within a Research Infrastructure? No Offer Description Indefinite-term
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Date 30 Oct 2025 Is the job funded through the EU Research Framework Programme? Other EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description We
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aim of this research is to develop new artificial intelligence algorithms that consume few computational resources. The person hired will focus their work on one or more of the following sub-lines