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Networks and Services (PONS) Research Unit (https://www.cttc.cat/packet-optical-networks-and-services-pons/ ) is looking for a PhD candidate to actively participate in the team activities in the framework
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processing image datasets for individual and behavior detection. - Defining, training, and validating Machine Learning models. - Collaborating in general research tasks. Where to apply Website https
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inteligencia artificial/machine learning. Tecnologías IoT y sistemas distribuidos. Conocimientos en FPGA. // Knowledge of artificial intelligence/machine learning, oT technologies and distributed systems, and
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deliverables writing, ability to work independently. Requisitos: Conocimientos de inteligencia artificial/machine learning. Diseño software, Gestión de datos, Arquitecturas backend (microservicios), Gestión de
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Technical Competences: Programming fundamentals: Python, Java, C, C++. Basic principles in techniques in Machine Learning frameworks: TensorFlow, PyTorch. Basic fundamentals in software engineering tools: MS
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processing of "Whole Slide Images". Other requirements to consider: Teamwork. Analyze complex problems and find innovative solutions. Specific Requirements Educational Requirements: Machine learning. Deep
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that will be used in the laboratory's tasks. Knowledge of new machine learning methodologies such as deep learning is required. Previous knowledge in the field of health sciences or research will be
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Requirements Educational Requirements: Test automation. Machine learning and data processing. IP protocols for satellite network communications. Professional Experience: In the E2E (end to end) verification and
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Educational Requirements: Machine learning. Neural Networks. Generalization of networks in different data domains. Training and inference in neural networks. Multimodal sensor data fusion. Visual recognition in
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expertise in data science, machine/deep learning, biomedical informatics, trustworthy AI, and health-related applications. The research group has an established track record in coordination and participation