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About the Role The project “An Erlangen Programme for AI” (funded by the UKRI), will broadly involve applying advanced mathematical techniques for understanding training in neural networks, with
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world networks have a multidimensional nature such as networks that contain multiple connections. For instance, transport networks in a country when considering different means of transportation
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on identifying the brain regions associated with different cognitive processes, but more recent studies seek to understand the nature of the information stored in various brain regions, or representations, and how
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networks, with a focus on carbon emissions reduction and network telemetry. You will contribute to the development of a framework that reduces the carbon emissions of networks through the use of carbon-aware
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funded by UKRI EPSRC and is fixed term for 12 months. You will be contributing to joint UKRI EPSRC – NSF CBET project on sustainable computer networks, with a focus on carbon emissions reduction and
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Lomet, Research Engineer in AI at LIAD, CEA Saclay · Marianne Clausel (University of Lorraine), scientific lead of the national PEPR causali-t-ai program, · Myriam Tami, Associate Professor
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models for signal transmission and reception, derivation of fundamental performance limits, algorithmic-level system design, and performance evaluation through computer simulations and/or experimental
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for IoT Wireless Sensor Networks Project Overview: We are looking for an outstanding Postdoctoral Researcher to join our ERC-funded project focused on solving one of the most pressing challenges in
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of efficient and robust neural networks. About your role: Independent research in the area of mathematics of machine learning, focusing on the development as well as the analysis of different algorithms and
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on the networked interactions between stakeholders in regional innovation ecosystems and assessing effects of interventions in such networks. We are interested in understanding the role of stakeholders in the set-up