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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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UNIVERSIDAD CATÓLICA DE MURCIA - FUNDACIÓN UNIVERSITARIA SAN ANTONIO DE MURCIA | Spain | 14 days ago
, development, and training of machine learning and deep learning algorithms. Creation of accurate, robust, and energy-efficient models. Development of systems capable of predicting and making decisions in real
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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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/Qualifications Experience in: - Development of artificial intelligent algorithms. - Explanaible artificial intelligence - LLM experience - Virtual intelligence entities using reinforced learning
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, integrated circuit designers, and quantum algorithm developers Analyze and interpret experimental data, contributing to scientific publications, patents, and presentations. Engage with the wider international
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FOR DRAWING UP OF PREDOCTORAL CONTRACTS FOR THE TRAINING OF DOCTORAL STUDENTS FUNDED BY THE UPV'S RESEARCH STRUCTURES – SUBPROGRAMME 2 (PAID-01-22) 119865 Development of machine-learning and graph-based models
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STUDENTS FUNDED BY THE UPV'S RESEARCH STRUCTURES – SUBPROGRAMME 2 (PAID-01-22) 119977 Development of mathematical and machine-learning algorithms to support an intelligent, integrated system for biosafety
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implementation of security provisioning algorithm in DFL environment Where to apply Website https://sede.uvigo.gal/public/catalog-detail/28364578 Requirements Research FieldEngineering » Communication
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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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doctoral programme coordinated by the UAB, designed to recruit and train 25 doctoral candidates. The programme focuses on advanced materials, innovative methodologies, and transformative solutions