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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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The SigCom research group of SnT, headed by Prof. Symeon Chatzinotas, focuses on wireless/satellite communications and networking. The research areas focus on the formulation, modeling, design, and
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Postdoctoral Researchers – Biochar, Syngas, Green Hydrogen & Net-Zero Heat Systems Specialization: Advanced Electrochemistry, Integrated Spectroscopy & Net-Zero Applications Locations: IAAM Net
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' to develop neural networks with remarkable information content: flies, which we use as a model, have brains that compute flying in 3D, navigation, metabolism and advanced learning and memory capabilities - all
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expertise covering mathematics, engineering, computer science and social sciences. We offer excellent working conditions in an international and stimulating environment, along with frequent opportunities
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Max Planck Institute for Dynamics of Complex Technical Systems, Magdeburg | Magdeburg, Sachsen Anhalt | Germany | about 1 hour ago
of Biological Networks at the Max Planck Institute for Dynamics of Complex Technical Systems in Magdeburg (Germany). Our group develops computational methods and tools for analyzing and redesigning
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diverse academic backgrounds to contribute to our projects in areas such as: Network Security, Information Assurance, Model-driven Security, Cloud Computing, Cryptography, Satellite Systems, Vehicular
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through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Communications in vehicular networks
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Arab Emirates Application Deadline 26 Nov 2025 - 00:00 (UTC) Type of Contract Permanent Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is
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Information content of brain wiring', funded by the Volkswagen Foundation Pioneering Research Program 'the unknown unknown.' The basic premise is simple: The information content of artificial neuronal networks