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Requirements Educational Requirements: Artificial Intelligence. Deep Learning. Computer vision. Reasoning methods based on first-order logic. Design of complex computer systems. Professional Experience: In LLM
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and Hugging Face. – Working with machine and deep learning models, including recurrent neural networks (RNNs), transformers and embedding techniques (Word2Vec, GloVe, BERT). – Designing and
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meetings at the University of Alicante. 2.6. Tasks to be carried out: Design and development of machine and deep learning models. Processing of volumetric data and images. Extraction of biomedical markers
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theory and experiment. By integrating quantum optics, quantum information theory, and machine learning, the project seeks to establish scalable hybrid spin–orbit quantum links. Free-space connections
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scale. Co-develop, apply and validate machine learning models from basin to regional scales. Where to apply Website https://seuelectronica.upc.edu/en/procedures/call-for-recruitment-of-research-s
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physicsEducation LevelMaster Degree or equivalent Skills/Qualifications A Master’s Degree in Physics or similar. Specific Requirements Experience in big-data management and analysis, with solid machine learning
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Description Develop the doctoral thesis focused on Quantum Computing and Machine Learning for Power Systems Where to apply E-mail monica.aragues@upc.edu Requirements Research FieldEngineering » Industrial
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scalable and efficient software and firmware analysis methodologies using tools like Frida or IDA Pro, enhanced with traffic monitoring techniques and Machine Learning to detect and analyze vulnerabilities
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analysis will not be considered. Programming Skills in Python, R, MATLAB Prior knowledge of Statistics and Machine Learning Competencies and skills: Communication, Teamwork and collaboration, Commitment
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incorporates probabilistic prediction models and hybrid optimization and machine learning techniques. This approach will enable the efficient assessment, planning, and offering of flexibility in scenarios