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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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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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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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modern control theory (PID, adaptive, robust, and fractional control); Experience with fuzzy logic and AI-based control (reinforcement learning, neuro-fuzzy systems); Skills in modelling and simulation
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applications to this selection procedure, provided they hold a doctoral degree* in Mathematical Logic, Set Theory or similar areas, and fully comply with the following requirements: Demonstrated scientific and
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; Essential knowledge of data analysis and measurement theory (e.g., noise, calibrations, uncertainty analysis statistics). Other Valued Skills Electronics design and production (e.g., KiCAD, Altium); Knowledge
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and Technical Skills Strong expertise in CMOS analog/mixed-signal design and simulation using industry-standard EDA tools (e.g., Cadence, Synopsys, Siemens); Deep understanding of analog circuit theory
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the following mandatory requirements: a) A completed degree in Chemical and Biological Engineering; b) Good knowledge in the areas of Machine Learning, Microbiology, Knowledge Graphs, and Language
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LIP - Laboratório de Instrumentação e Física Experimental de Partículas | Portugal | about 2 months ago
Skills/Qualifications Demonstrable knowledge of Quantum Mechanics, Particle Physics and Quantum Field Theory. Specific Requirements Previous experience on Quantum Chromodynamics, namely parton showers and
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the development of deep learning models based on graphs and images (EXP) – 0 to 20 values Specific competencies for the proposed work plan (CEPTP): With a maximum weighting of 30%. Demonstrated practical knowledge