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Field
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Infrastructure? No Offer Description Area of research: Promotion Job description: Your Job: Analysis of market dynamics in the context of Innovation Ecosystems and Diffusion Theory Systematic integration
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machine learning techniques to develop local graph representation models, which will be aggregated globally to enhance their predictive power and translational relevance, all while maintaining strict data
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environmental disaster (climate change) for another (ecosystem damage). A circular economy for EVs, which seeks to recover waste at all stages of the life cycle, has been proposed as a partial solution to curb
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and magnetic fields. A crucial aspect lies in the interpretation/modelling of the results. In this role, you will get to work with a variety of devices structures, with an emphasis on quantifying
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team using the contact information below. The Role We are looking for a diagnostic R&D scientist to be part of the Cell Models and Antibody Technology team within our Medical Devices Research Centre (MD
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at the interface between stochastic modelling, signal processing and data science. Ultimately, the project will develop key indices that can be used to assess the health of the soil ecosystem. Such indices
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fundamentals of networking. Objectives: To achieve on-device spectrum sensing using on-board sensors of mobile BSs, empowered by embedded deep learning algorithms; to propose an analytical model for the cell
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of computer-assisted orthopedic surgery, embedded in Zurich’s vibrant MedTech and AI ecosystem. With direct access to the state-of-the-art OR-X infrastructure for translational validation, the successful
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of industrial ecosystems surrounding AM in the Netherlands, examining how firms, institutions, and infrastructures interact to enable—or constrain—the development of a competitive and sustainable AM sector
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management. The research will directly contribute to the agroecological transition, seeking to align productive efficiency with ecosystem preservation and the reduction of both water and carbon footprints