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for this grant, a requirement to be duly proven at the time of hiring. Activity Outline: Research activities in the area of applying Machine Learning in the context of Industry 4.0. Study of using Machine Learning
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for this grant, a requirement to be duly proven at the time of hiring. Activity Outline: Research activities in the area of Embedded Systems for the execution of Machine Learning algorithms. Legislation and
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for this grant, a requirement to be duly proven at the time of hiring. Activity Outline: Research activities in the area of Embedded Systems for the execution of Machine Learning algorithms. Legislation and
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this call may apply for this grant, a requirement to be duly proven at the time of hiring. Work plan: Research activities in the field of reinforcement learning for unmanned aerial vehicles. Applicable
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Computer Engineering or related areas; Knowledge of the development of automatic [deep] learning and information visualization applications; Experience in the use of algorithms and data analysis methods
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to the following conditions: Work plan: The successful candidate will contribute to developing a context-aware machine learning-based predictive framework to be used in the context of applications to automate
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Operating System (ROS). Some experience on robotics, machine learning, AI, coding. Motivation, sense of responsibility, autonomy and problem-solving skills are highly desirable. LanguagesENGLISHLevelExcellent
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; • High organizational capacity and work methodology; • Willingness to evolve and acquire new knowledge. APPLICATION SUBMISSION The call is open from March 14 until 11:59 PM on March 31, 2025. Only
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; • Strong motivation, autonomy, and proactivity; • Results-oriented and problem-solving skills; • High organizational capacity and work methodology; • Willingness to evolve and acquire new knowledge
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Instituto de Investigação e Inovação em Saúde da Universidade do Porto (i3S) | Portugal | 2 months ago
assessment, and an analysis module that provides useful information for the user's health through multimodal signal analysis supported by machine learning/artificial intelligence techniques. In this project