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Field
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methods for load identification and modelling to infer load behaviour from measurements at the grid supply point (GSP). Your work will help determine whether new load types need to be defined in the CLM
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behavioral neuroscience or signal processing (especially of bioacoustics data) Programming experience (e.g. Python, R, Matlab, etc.) Strong communication and collaborative skills and proficiency in spoken and
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, for the scientific areas of Biomedicine, subarea of Cancer nanomedicine, at the University of Coimbra. This tender is open within the scope of the project with reference number 16012 - Operation Code: COMPETE2030
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that require ultra low power operation. In both projects we will work closely together with experts in electronic circuit design to realize the electronic interfacing for the sensors, in case of the flow sensors
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of Communication Systems carries out research, undergraduate and postgraduate education. We conduct research and education in communications engineering, statistical signal processing, network science, and
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the remarkable spatial perception of bats. By leveraging array signal processing to synthesize morphology-induced HRTFs without physical replicas, the project offers a flexible, high-fidelity and scalable approach
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and reliability. You will integrate, adapt and develop methods (using packages such as BioSPPy) for the processing and analysis of physiological signals measured for determining deception. The project
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modelling to infer load behaviour from measurements at the grid supply point (GSP). Your work will help determine whether new load types need to be defined in the CLM framework to accommodate new components
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master's level (corresponding to the 3 + 2 Bologna process) have received the grade of 10 (or equivalent) for the master's thesis according to the Danish 7-point grading scale (https://ufm.dk/en/education
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for the programme will be 5,000 EUR per study year. Combined Master's degree / PhD programme No Joint degree / double degree programme Yes Description/content Globalisation processes are strongly linked to issues