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PhD Scholarship – Modelling the social and political drivers of net zero transitions Job No.: 670767 Location: Clayton campus Employment Type: Full-time Duration: 3.5-year fixed-term appointment
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11.11.2024, Wissenschaftliches Personal In the project “BIG-ROHU” (BIG Data - Rotor Health and Usage Monitoring), a system is being developed which provides information on both the health and the actual stress of helicopter components using a data-based as well as a physics-based approach. In...
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, the internal workings of deep neural networks remain largely mysterious, posing a significant challenge to the interpretability, reliability, and further advancement of these models. This project seeks deep
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Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Marie Sklodowska-Curie Action (MSCA) Doctoral Networks
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role in intracellular transport. As such, they play an important role in nuclear positioning. Our team is studying, in a developmental context, how multiple microtubule networks cooperate to position
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of multicore fibre (MCF) technology.MATCH (Multicore Fiber - Applications and Technologies - Match) is a Marie Sklodowska-Curie doctoral network funded by the European Commission under the Horizon Europe. MATCH
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of Sassari (UNISS) is seeking for a Doctoral candidate (DC) to be enrolled as PhD student in the MSCA Doctoral Network (DN) METAMIC 3 (Metaproteome-based leveraged microbiome management in the context of One
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Number BAP-2025-545 Is the Job related to staff position within a Research Infrastructure? No Offer Description This PhD is part of the Marie Skłodowska-Curie Doctoral Network “MAGNIFY” and aims to tackle
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: Develop an event-driven RL algorithm that sparsely updates network state and parameters that will significantly improve energy to-solution efficiency compared to conventional digital accelerators when
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engineering, computational neuroscience, artificial neural networks and bio-inspired robotics: "Rhythmic-reactive regulation for robotic locomotion" (Supervisor: Prof Fulvio Forni) will apply techniques from