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18 Sep 2025 Job Information Organisation/Company International Iberian Nanotechnology Laboratory (INL) Research Field Physics Mathematics Researcher Profile First Stage Researcher (R1) Positions Postdoc Positions Country Portugal Application Deadline 8 Oct 2025 - 23:00 (Europe/Lisbon) Type of...
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methodology for designing asynchronous circuits using Workcraft software, based on Signal Transition Graphs (STG). The objective is to generate the STG description from a state and transition diagram and/or
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.; Minimum requirements: -Agricultura de precisão e digital. - BS: ‘genome scale metabolic models’, ‘graph analysis’, ‘flux balance analysis’ - Modelos preditivos baseados em AI. - Computacionais: R
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related fields. Proven expertise in knowledge knowledge graphs (KGs), demonstrated by the successful completion of detailing the curricular units in the area. Additional optional skills and qualifications
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. This scholarship aims to support PhD-level studies on FAE by exploiting a new methodology that combines deep learning technology and knowledge graphs. The goal is to research and develop a new Decision Support
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in those complex systems and related concepts. As part of this study, the researcher wilt be required to develop Python freeware to analyze and visualize graphs aiming towards explainability of dynamic
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, as well as probabilistic reasoning, PageRank-based classification, and rule extraction via knowledge graphs. To promote transparency and trust, model interpretability will be carefully assessed using
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by the European Research Council - ERC COG 101088763. The work for this position is in the area of Machine Learning, Decision Theory, Reinforcement Learning. Scientific Area: Information and Data
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Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID | Portugal | about 1 month ago
physics and string theory, with emphasis on resurgence as applied to random matrix theory, in particular the computation of correlation functions in the N=2 JT and the ABJM matrix models. Duration
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on the applicants' enrolment in study cycle or non-award courses of Higher Education Institutions. Preference factors: Experience in musical audio machine learning frameworks, advanced knowledge in music theory, and