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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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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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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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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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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
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TRAINING: Literature review on anomaly detection in network data; Using deep learning to detect anomalies in network data flows.; 4. REQUIRED PROFILE: Admission requirements: Degree in Computer Engineering
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results. 3. BRIEF PRESENTATION OF THE WORK PROGRAMME AND TRAINING: - Develop machine learning-based models from data.; - Validate the developed models with real data.; - Publicize the work in international