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, in collaboration with the team responsible for the development of the ApneaScreener algorithm. Knowledge of data analysis tools, particularly Python and R, will be valued to support the interpretation
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in LIBS systems.; • Develop algorithms for correction and compensation of galvanometric scanning, ensuring accurate spatial correspondence of LIBS data.; • Implement automated pipelines for LIBS data
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Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID | Portugal | about 1 month ago
, financed by EU and national funds through FCT/MCTES (PIDDAC Workplan: Machine learning algorithms, in particular deep learning ones, suffer from the phenomena of catastrophic forgetting, which hampers
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value candidates with interest and/or experience in the following areas: a) Understanding of machine learning techniques, with interest in exploring algorithms such as regression, decision trees, Random
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of Electromechanical Engineering, under the following conditions: Research Field: Informatics Engineering relaed fields Objectives: The objective of this grant is: (1) to support the programming of AI algorithms
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of Electrical Engineering or related areas. - In addition, the candidate should demonstrate solid knowledge in electric power systems and in the development of optimization algorithms and intelligent systems
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Engineering or related fields. - A solid background in electric power systems is required, as well as experience in the development of optimization algorithms and intelligent systems. - The ability to apply
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the communication system for prototypes of the autonomous monitoring system for invasive wasp species (Asian hornet); (2) to support the programming of AI algorithms for image recognition; (3) to develop the web
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: Alexandre José Malheiro Bernardino (ist13761) Organic Unit: Institute of Systems and Robotics Scholarship Theme: Research in object search algorithms for autonomous robots Duration: 6 months Maximum Duration
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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