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description: Work Area: Research and development of new algorithms for processing and classifying physiological signals in ambulatory systems Project overview: Processing of physiological and inertial signals
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Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID | Portugal | 3 days ago
, reference no. 2023.18249.ICDT, financed by national funds through FCT/MCTES (PIDDAC Workplan: Development of methodologies and machine learning algorithms for the detection of anomalous behaviors in flow rate
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Advisor: Ana Paula Martins Falcão Flor (ist13814) Co-advisor(s): Jónatas Valença (ist417176), LNEC. Organic Unit: Scientific Area of Construction Scholarship Theme: The work aims the development
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Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID | Portugal | 3 days ago
, reference no. 2023.18249.ICDT, financed by national funds through FCT/MCTES (PIDDAC Workplan: Development of new algorithms based on statistical analysis for the detection of bursts in water distribution
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Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID | Portugal | 3 days ago
sensor integration, building a simple 2-finger motorized prototype, and developing perception-to-control algorithms. The prototype will be electrically/kinematically compatible with iCub and Vizzy humanoid
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the radiosensitivity of patients. 3) Expansion of the algorithms developed to include fractionation as an optimization variable. Legislation framework: Research Fellowship Holder Statute, in accordance with Law 40/2004
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for applications for one research grant within the framework of project ISA4RL - Integrating Instance Space Analysis with Auto-Reinforcement Learning for Adaptive Algorithm Selection and Configuration
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-inspired selection). 3-Investigate the integration of QIEC with Quality-Diversity (QD) algorithms such as MAP-Elites.(month 2-3) 4-Explore the use of Evolutionary Computation to generate and optimize quantum
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.pdf JOB ADVERTISEMENT Recruitment of 1 Doctorate in the field of Research and development of new algorithms for processing and classifying physiological signals in ambulatory systems INESC TEC
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and signature matching based on existing code. - Performance evaluation of the application on a Raspberry Pi (RPi). - Development of improvements to machine learning algorithms for anomaly detection and