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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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of the state of the art in machine learning for generation of artificial data; - identify and select the appropriate methods for the study in question; - develop the research capacity through the application
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domain in the design of deep learning algorithms for cardiovascular disease detection. 4. REQUIRED PROFILE: Admission requirements: Master’s degree in Biomedical Engineering, Computer Engineering
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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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models to characterize lung cancer based on a non-invasive methodology. 3. BRIEF PRESENTATION OF THE WORK PROGRAMME AND TRAINING: - extend the knowledge of the state of the art in machine learning
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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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21 Nov 2025 Job Information Organisation/Company INESC TEC Research Field Engineering » Computer engineering Engineering » Electrical engineering Researcher Profile First Stage Researcher (R1
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benefit from health insurance, supported by INESC TEC. 2. OBJECTIVES: ● Research and develop novel reliable deep learning computer vision algorithms for the detection and quantification of GIM lesions
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-bolseirosEN ) The grant holder will benefit from health insurance, supported by INESC TEC. 2. OBJECTIVES: 1. Formulate and validate automated inspection methodologies based on computer vision and AI techniques
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manipulators capable of adjusting their trajectory and resistance in real time in response to variable external loads. This module should integrate learning algorithms based on artificial intelligence, allowing