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: Fraunhofer Portugal AWAM, Vila Real, Portugal, under the scientific supervision of PhD Mara Silva. Scholarship’s Duration and Regime: The scholarship shall have a duration of 6 months, eventually renewable
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on the development of methodologies and techniques of Evolutionary Computation and Machine Learning. V - Initial grant duration: 3 months V.I - Renewal Possibility: Possibily renewable VI - Funding and financial
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Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID | Portugal | about 1 month ago
. The candidate(s) may also be required to apply data fitting algorithms/machine learning algorithms to link models to biological data from the literature. The project integrates elements from dynamical systems
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Stage Researcher (R1) Positions PhD Positions Application Deadline 23 Apr 2026 - 23:59 (Europe/Lisbon) Country Portugal Type of Contract Temporary Job Status Full-time Hours Per Week 35 Offer Starting
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Stage Researcher (R1) Positions PhD Positions Application Deadline 23 Apr 2026 - 23:59 (Europe/Lisbon) Country Portugal Type of Contract Temporary Job Status Full-time Hours Per Week 35 Offer Starting
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than 14/20 (1 point); B. Knowledge of Interactive Systems Design, Cyber-Physical Systems, Predictive Maintenance Systems, Automation, Machine Learning and Artificial Intelligence, Sensor Networks
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EXPERIMENTAL, NUMERICAL AND MACHINE LEARNING”, funded by the “Programme, Innovation and Digital Transition (Compete 2030), European Regional Development Fund FEDER and national funds, Portugal 2030, Foundation
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recognition, if applicable). - Enrollment in a PhD program. Specific Requirements - Master's degree in Environment Engineering, or related areas (If the candidate holds a higher education degree obtained abroad
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Engineering or Industrial Engineering and Management) - 10 points; Others Masters – 2 points) b) Experience in applying machine learning algorithms, data preparation, normalization, feature selection, and
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machine-learning methods for sample segmentation and classification. 3. BRIEF PRESENTATION OF THE WORK PROGRAMME AND TRAINING: The fellow will join the INESC TEC team within the LIBScan project, carrying