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Field
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, multisensory integration, or visual perception) using data analysis and machine learning techniques. Implement XR prototypes and applications to validate the developed models. Contribute to the publication
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advanced instrumentation (ACSM, Xact, SMPS…) and machine-learning techniques. The selected candidate will work in a multidisciplinary and international research environment, contributing to the assessment
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biomechanical signals (e.g., EEG, EMG, ECG, eye tracking, inertial sensors). Programming skills in Python and/or MATLAB; familiarity with machine learning frameworks. Experience in sensor integration, real-time
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Engineering, or a related field with a strong academic background in Machine learning, Natural Language Processing, and/or Software Development. Applicants with an experience in one or more of the above
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Skills/Qualifications A Bachelor Degree or an equivalent in Computer Science, Telecommunication Engineering, or a related field with a strong academic background in Machine learning, Natural
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programme Is the Job related to staff position within a Research Infrastructure? No Offer Description in charge of the research line: «Machine learning for remote sensing image processing (ML4RSIP)». Junior
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Experience with single-cell and/or high-throughput sequencing analyses Experience with data analysis and machine learning Use of version control software and GitHub Experience working with Linux environment
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. The successful candidate will be involved in the gravitational wave astronomy research area as part of the GRAVITY research group, within the framework of the project "Ground-based Discovery Machines
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and error quantification of models reduced-order models (ROMs) based on Machine Learning (ML) with applications to aircraft design. - Software development. - Writing of technical reports and/or
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Pastrana, Guillermo Suarez-Tangil. IoC Stalker: Early Detection of Indicators of Compromise. Annual Computer Security Applications Conference (ACSAC). December 9–13, 2024. (link: https://suarez