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the project ‘MultiLearn: A multimodal approach to language learning: a window into the linguistic skills of children with neurodevelopmental disorders‘. The project is led by researchers Alfonso Igualada and
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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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analysis, including statistics and machine learning techniques. Proficiency in scientific programming, especially Python and/or Matlab, and experience in shell scripting. Excellent written and oral
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Basque Center for Macromolecular Design and Engineering POLYMAT Fundazioa | Spain | about 1 month ago
(Python, Matlab, etc.) as well as in modeling polymerization processes or using machine learning techniques is highly desirable. Good command of written and spoken English is a must (if preselected, an
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networks and in mobile & edge computing platforms. Where to apply Website https://networks.imdea.org/job/phd-position-on-safe-machine-learning-msca-final… Requirements Research FieldEngineering » Electrical
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. Preliminary exposure to machine/deep learning, statistical modelling or generative AI. Application process: Interested candidates are invited to apply via the PHYNEST online platform by submitting a full CV, a
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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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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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Basque Center for Macromolecular Design and Engineering, POLYMAT Fundazioa | Spain | about 1 month ago
programming (Python, Matlab, etc.) as well as in modeling polymerization processes or using machine learning techniques is highly desirable. Good command of written and spoken English is a must (if preselected
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classification of EEG and auditory signals. The group of the project is multidisciplinary, with experts in signal processing, machine learning, acoustics and language. The successful applicant will perform