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) The grant holder will benefit from health insurance, supported by INESC TEC. 2. OBJECTIVES: Development of novel Machine Learning techniques applied in systems/networks research, which includes, but is not
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support the conversion and modernization of packages developed in ROS1 to ROS2 in the laboratory. The fellow will collaborate with the members and those responsible for the original packages, ensuring
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PROGRAMME AND TRAINING: - extend the knowledge of the state of the art in machine learning for lung cancer imaging data; - identify and select the appropriate methods for the study in question; - develop
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TEC. 2. OBJECTIVES: - Expand knowledge in the grant-specific scientific area.; - Identify and select appropriate methods for the target study.; - Develop research capability through the application
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to the scientific tasks of the project CINDERELLA in medical image analysis; - Identify and select appropriate methods for object detection in medical images ; - Develop research skills through the application
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advanced industrial analytics. Objectives: Contribute to applied research on data governance frameworks, digital platforms, and data spaces. Activities include developing case studies with industry partners
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-bolseirosEN ) The grant holder will benefit from health insurance, supported by INESC TEC. 2. OBJECTIVES: Develop control solutions for the IRIS autonomous underwater vehicle to collect lost networks Study and
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acoustic detection system; 2. Implement underwater triangulation location systems; 3. Identify patterns of biological (e.g., cetaceans) and human (e.g., vessels) activity; 4. Plan, prepare, and participate
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-scaling architectures; - identify and select methods for researching, developing and validating the target topics; - develop research and prototypes using complex real-world architectures as case studies
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architectures for the energy and power management system on ships Develop control and dispatch strategies for hybrid microgrids, taking into account the specific power and energy requirements of ships Modeling