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                Employer- BCBL BASQUE CENTER ON COGNITION BRAIN AND LANGUAGE
- Centre Tecnològic de Telecomunicacions de Catalunya (CTTC)
- IMDEA Networks Institute
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- BCBL - Basque Center on Cognition, Brain and Language
- Centre for Genomic Regulation
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                working on challenging theoretical and practical problems in Safe Machine Learning. Specifically, we are looking for a student to address the following research problem in their PhD thesis: 1 
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                EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Reference: 596_25_LS_ESB_R1 Job title: PhD student in computational biophysics and machine 
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                Other Researcher Profile First Stage Researcher (R1) Positions PhD Positions Country Spain Application Deadline 8 Oct 2025 - 23:59 (Europe/Madrid) Type of Contract Temporary Job Status Full-time Hours Per 
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                participative digital platform that encourages users to contribute through crowdsourcing, oral interviews, or sharing privately held materials. Implementation of AI and machine learning techniques, including 
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                processing (computer vision & machine learning) Where to apply Website https://sede.uvigo.gal/public/catalog-detail/28364578 Requirements Research FieldEngineering » OtherEducation LevelMaster Degree 
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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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                ) and satellite platforms, and surface energy balance models will be used to obtain evapotranspiration (ET); computer vision and machine learning techniques will also be used to identify and count fruits 
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                Researcher (R3) Positions PhD Positions Country Spain Application Deadline 22 Nov 2025 - 23:59 (UTC) Type of Contract Permanent Job Status Full-time Hours Per Week 37.5 Is the job funded through the EU 
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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 
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                of AI and machine learning techniques, including handwritten text recognition and probabilistic indexing, to improve access to historical sources. Ensuring the archive is sustainable, accessible, and