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, that the candidate considers more relevant or with greater impact in order to allow the corresponding relevance, quality, timeliness and adequacy. - Copy of certificates or diplomas degree - Other documents that you
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algorithms; - Automation of the model customization process by conducting laboratory tests.; - Improvement of the data workflow for real-time processing and sharing.; - Data collection in experimental and real
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of genAI systems, simulation and Digital Twins, with corresponding back-end and front-end implementation. Academic Qualifications: Master's degree in Computer Engineering or equivalent Minimum profile
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are:; - Developing energy consumption forecasting tools based on real data.; - Applying these tools to a use case.; - Writing reports and articles for international conferences and journals using the new models and
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underwater positioning systems; b. Acoustic propagation models (propagation delays, acoustic range, "multipath", etc.); c. Error sources and correction; 2. Synchronization of remote monitoring systems; 3
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/pagamento-propinas-bolseirosEN ) The grant holder will benefit from health insurance, supported by INESC TEC. 2. OBJECTIVES: • modelling and optimisation of PCM thermal storage for buildings and industry use
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electrical engineering projects.; - Knowledge of libraries for developing and training ML models; Minimum requirements: - Knowledge of computer programming. 5. EVALUATION OF APPLICATIONS AND SELECTION PROCESS
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of inertial underwater navigation and dynamic flow measurement systems; - Development of a flow and pressure sensor array on a flexible PCB (print circuit board); - Development of instrumentation and a
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-resolution mechanisms of hash tables using linked lists and dynamic arrays; development of test cases to validate the implemented techniques.; 4. REQUIRED PROFILE: Admission requirements: Bachelor's degree in
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the generated data can be used in practice. A new metric to help this comparison is expected to be created. 3. BRIEF PRESENTATION OF THE WORK PROGRAMME AND TRAINING: Test GAN models – Compare leading GANs