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                for admission to the AFAM PhD Course in Music, Design, Art, Territories 41th cycle - academic year 2025/2026 6 positions available The associated AFAM Research PhD in Music, Design, Art, Territories (lead partner 
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                Music, Performance and Technological Innovation addresses strategic issues related to the concept of performance and musical creation through interdisciplinary research and training, capable 
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                , to decrease our dependence on fossil fuels. Energy Geostructures (EGs) represent an effective means to meet the world request of less dependence on unsustainable resources by being designed as dual-purpose 
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                of periodic chiral systems and improve current software limits. ii) design computational protocols to perform applications of the developed software. Expected Results: simulate, predict and rationalise 
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                3 Oct 2025 Job Information Organisation/Company Edmund Mach Foundation Department Research and Innovation Centre Research Field Computer science Physics Engineering Mathematics Information science 
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                Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description PhD in Politics is designed for researchers who want to work in 
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                listed below: 1) Cities and Landscapes: Architecture, Archaeology, Cultural Heritage, History andResources 2) Engineering for Innovation and Sustainable Development 3) Science 4) Agricultural, Forestry and 
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                provided aim to offer methodologies useful for the design and implementation of the research project, with a clear general structure — based on the recognition of a solid research question and the 
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                alloys with different experimental techniques Design surfaces with enhanced antibacterial properties Evaluate the cytocompatibility and the antibacterial activity of the produced alloys and surfaces 
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                multiple-output) for high data rate and reliability, integrates semantic and goal-oriented communication, and leverages physics-informed machine learning. A key innovation will be the development