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Researcher, of the FCiências.ID Scientific Research Career, within the scope of the project HOFGA: The Hardness of Finding Good Algorithms (Ref. HORIZON-ERC-STG-101041696), financed by the European Union´s
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analysis, AI algorithm modeling, testing, and integration into functional systems within the project scope. Specifically, in activities related to behavior modeling from IoT device data, generative AI
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seeking a senior postdoctoral researcher (R2 level) to take on a leading technical role in the development of advanced modelling, control and optimization tools for smart energy systems. The selected
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, the selected researchers will deal with: Research & Development: Designing, developing, and implementing state-of-the-art machine vision and deep learning algorithms to analyze complex image and sensor data
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coalitions for delivering reliable, low-carbon energy services. Collaborating closely with UK Power Networks, SSE Energy Solutions, and the University of East London, you will develop robust economic Model
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Trondheim, Norway, but the Researcher-project is of both academic and industrial relevance, and it will therefore be developed in close cooperation between NTNU in Trondheim and the company Petronas, which is
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participate in the training and dissemination events of the MSCA Doctoral Network ANT . You will develop signal processing algorithms and protocols for AirComp, and implement and validate them in simulation
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require the design of architectures suitable for real-life problems. Moreover, appropriate mathematical methods, algorithms, and applications are required. Simulators are a recognized method for
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Carl von Ossietzky Universität Oldenburg | Oldenburg Oldenburg, Niedersachsen | Germany | about 2 months ago
conservation related consequences of animal navigation, and (4) links biological and technical systems through models, algorithms, and devices. The acquired knowledge can help to solve major societal questions
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deep learning and scalable deployment Collaborate with researchers, developers, and traders to improve existing models and explore new algorithmic approaches Design and run experiments using the latest