206 network-coding-"Chung-Ang-University"-"Chung-Ang-University" Postdoctoral positions in United Kingdom
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.) if candidate holds a relevant degree and is working on PhD/DPhil) together with established knowledge in wired computer networks and sustainable computing, significant coding experience (both Python and C/C
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/DPhil) together with established knowledge in wired computer networks and sustainable computing, significant coding experience (both Python and C/C++), and a record of working in a Linux environment and
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networks. This position is part of a UK-Canada Quantum for Science collaborative project "Quantum network applications in theory and practice" funded by STFC/EPSRC (UK) and NSERC (Canada), led by Professor
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. Ready to be part of our team? Let’s shape the future together! Your personal sphere of play: The Department of Network Biology at the University of Vienna is seeking a highly motivated Postdoctoral
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crystalline resins for use in two-photon polymerization. New forms of imaging hardware will be utilized in collaboration with partners to provide greater understanding of the polymer network morphology and how
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understanding of the polymer network morphology and how it relates to the laser process parameters. Specifically, you will carry out high resolution Raman imaging on laser written polymer networks with liquid
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aims to optimize the operations (serving) of AI by developing algorithms that manage compute, network, and storage resources in a carbon-efficient way while supporting long-term benefits
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research. As the hub of the new National Mouse Genetics Network, the specialist facilities and capabilities of the MLC support a number of research groups across the UK to accelerate our understanding
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, quantitative and qualitative data analysis; and working with a network of European collaborators (the EuroWISE collective). Work Package 2 (Analysis and Data Management): The PDRA will be responsible for data
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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