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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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-award courses of Higher Education Institutions. Preference factors: Machine Learning Knowledge. Knowledge of signal processing and machine learning libraries (e.g., PyCaret, scikit-learn). Minimum
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Institute of Systems and Robotics, Faculty of Sciences and Technology of the University of Coimbra | Portugal | about 1 month ago
Engineering Research Field Engineering » Electrical engineering Engineering » Electronic engineering Engineering » Mechanical engineering Engineering » Computer engineering Researcher Profile First Stage
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of Machine Learning techniques. 5. EVALUATION OF APPLICATIONS AND SELECTION PROCESS: Selection criteria and corresponding valuation: the first phase comprises the Academic Evaluation (AC), based
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the following mandatory requirements: a) A completed degree in Chemical and Biological Engineering; b) Good knowledge in the areas of Machine Learning, Microbiology, Knowledge Graphs, and Language
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optional skills and qualifications: Previous research experience, particularly in the fields of Internet of Things security and machine learning model security applied to intrusion detection. Contracting
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experience in the fields of HRI, robotics, computer vision, or machine learning. Programming skills. Contracting requirements: Presentation of the academic qualifications and/or diplomas, if applicable
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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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following mandatory requirements: a) A completed degree in Computer Engineering; b) Good knowledge in the areas of Machine Learning, Natural Language Models, and Computer Security – information to be provided
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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