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Field
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Algorithmic Categorization”, 2024.07707.IACDC supported by measure “RE-C05-i08.m04 – “Support the launch of a program of R&D projects aimed at the development and implementation of advanced cybersecurity
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) develop novel performance metrics combining accuracy and explainability, to be tested across different AI model types; (2) devise new algorithms for selecting models optimised for holistic performance
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. The PhD position will focus on developing a deep-learning algorithm for analyzing the acquired experimental data. The PhD position will focus on development a comprehensive and AI-driven platform
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Researcher will influence the direction of application areas and algorithm development, receiving direct training in InSAR processing, geospatial data science, and agricultural remote sensing. Co-supervision
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to humans and are accessible to algorithmic techniques while neural models are adaptive and learnable. The aim of this project is to develop models which combine these advantages. The project includes both
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) Interpretable machine learning for network adaptation. In this thesis, the student will study how interpretable models and explainable learning algorithms could be used in real cellular networks for safe
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. About your role: Develop improved physical models of the image formation process in holographic X-ray imaging Design and implement reconstruction algorithms for handling large-scale tomographic data from
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these technologies can only read DNA fragments of limited length. We enable biological interpretation of these sequencing data sets by developing algorithms based on graph theory, discrete optimization and machine
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while developing transferable skills in an international, interdisciplinary setting. The 15 open positions: DC1: Low-power IoT sensing at high frequency bands Host: IMDEA Networks Institute, Madrid, Spain
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data preprocessing, algorithm development, and optimization techniques. Excellent communication skills in English. Prior experience with environmental or photocatalytic systems is a plus. A fully funded