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) The grant holder will benefit from health insurance, supported by INESC TEC. 2. OBJECTIVES: The successful candidate will develop signal and image processing techniques, as well as apply machine learning
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: Experience in research projects, and writing of scientific papers. Minimum requirements: Experience in Computer Vision and machine learning. 5. EVALUATION OF APPLICATIONS AND SELECTION PROCESS: Selection
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new approach based on physically inspired hybrid machine learning models for generating artificial data using generative models. The result will be high-fidelity medical data. 3. BRIEF PRESENTATION
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TRAINING: - extend the knowledge of the state of the art in computer vision and machine learning for cancer characterization; - identify and select the appropriate methods for the study in question
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. Preference factors: Experience in research projects. Minimum requirements: Experience in Computer Vision and machine learning. 5. EVALUATION OF APPLICATIONS AND SELECTION PROCESS: Selection criteria and
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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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TRAINING: - survey the state of the art in emerging wireless networks, including their simulation using real data assimilation, machine learning, and digital twin approaches; - collaborate in the writing
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, supported by INESC TEC. 2. OBJECTIVES: The objectives for this grant are as follows:; • Research and develop machine learning algorithms for the processing of gastric endoscopy images.; • Lead or support the
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of the robot arm.; • Develop the software for the intelligent robotic programming module: implement algorithms (e.g. based on machine learning) for adaptive rehabilitation exercises; • Test and evaluate
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26 Feb 2025 Job Information Organisation/Company INESC TEC Research Field Engineering » Computer engineering Information science Researcher Profile First Stage Researcher (R1) Country Portugal