62 algorithm-development-"Multiple"-"Simons-Foundation"-"Prof" positions at INESC TEC in Portugal
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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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mathematics,Informatics Job summary: INESC TEC is accepting applications for 1 RESEARCHER job in the Software Engineering and API Development for Power Systems Project: Scientific Advisor: Tiago André Soares
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initiatives, particularly in the field of Energy Systems - Energy Transition. The objectives are:; - Development and application of artificial intelligence algorithms for different use cases in the energy
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://www.inesctec.pt/pagamento-propinas-bolseirosEN ) The grant holder will benefit from health insurance, supported by INESC TEC. 2. OBJECTIVES: - Development and testing of algorithms and methodologies based
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://www.inesctec.pt/pagamento-propinas-bolseirosEN ) The grant holder will benefit from health insurance, supported by INESC TEC. 2. OBJECTIVES: - Development and testing of algorithms and methodologies based
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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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. Implementation of signal detection algorithms and triangulation ; 4. Planning and participating in field tests to evaluate system performance; 5. Reporting and disseminating the work developed (ideally with a
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that provides AI-based suggestions. The work will consist in the improvement and evolution of previously developed models, as well as interacting with project partners to integrate algorithms and conduct field
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algorithms for analyzing electrocardiography, electromyography and movement signals, identifying characteristics and recognizing patterns in everyday activities. Testing and validation of methods developed in
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or international conference. 3. BRIEF PRESENTATION OF THE WORK PROGRAMME AND TRAINING: Research and development of algorithms for analyzing signals acquired in real time by a system with integrated