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applying CBA methodologies.; - Knowledge and experience with optimization; - Knowledge of Renewable Energy Communities (REC) operation; - Knowledge of operation of REC main assets (Heat Pump, Storage, PV
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, than can execute this type of task over geographically distributed data sets, under the administrative control of different entities.; The aim is to:; - Broaden knowledge of the state of the art in
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tools.; - Experience using HPC environments (e.g. SLURM).; Minimum requirements: - Solid knowledge of deep learning architectures and tools (i.e. TensorFlow, PyTorch, GANs, CNNs). - Solid knowledge
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: Knowledge in power system dynamics; Knowledge in modelling and simulation under MAtlab/Simulink or Power Factory DigSilent. 5. EVALUATION OF APPLICATIONS AND SELECTION PROCESS: Selection criteria and
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software, an IDE for programming microcontrollers and knowledge of signal processing algorithms, the aim is to develop the prototype of a new wearable device. This device will be tested and calibrated
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/pagamento-propinas-bolseirosEN ) The grant holder will benefit from health insurance, supported by INESC TEC. 2. OBJECTIVES: - extend the knowledge of the state of the art in the specific scientific area of
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holders" (https://www.inesctec.pt/pagamento-propinas-bolseirosEN ) The grant holder will benefit from health insurance, supported by INESC TEC. 2. OBJECTIVES: - Expand knowledge of the state of the art in
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TEC. 2. OBJECTIVES: - Enlarge knowledge of digital simulators state-of-the-art for power systems; - Develop the R&D capacity through the application of machine learning methods; - Develop research
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on the applicants' enrolment in study cycle or non-award courses of Higher Education Institutions. Preference factors: Enrolled in a Master's degree in Physics Engineering. Knowledge of programming in Labview and
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); Minimum requirements: - Knowledge in one programming language - Basic knowledge in data analysis, ICT and IoT 5. EVALUATION OF APPLICATIONS AND SELECTION PROCESS: Selection criteria and corresponding