56 parallel-and-distributed-computing-"DIFFER" positions at University of Exeter in United Kingdom
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to train tomorrow’s leaders in earth and environmental science. For further details about the programme please see http://nercgw4plus.ac.uk/ For eligible successful applicants, the studentships comprises
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PhD Studentship: Distributed and Lightweight Large Language Models for Aerial 6G Spectrum Management
such a promising technology, the centralised and resource-intensive nature of current LLMs conflicts with the constraints of aerial 6G networks in terms of limited computation, energy, and communication
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to train tomorrow’s leaders in earth and environmental science. For further details about the programme please see http://nercgw4plus.ac.uk/ For eligible successful applicants, the studentships comprises
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to train tomorrow’s leaders in earth and environmental science. For further details about the programme please see http://nercgw4plus.ac.uk/ For eligible successful applicants, the studentships comprises
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the TroPeaCC project. Applicants will be able to keep accurate records, be able to organise their work, be computer literate, have good analytical skills, good communication abilities l and will be able
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, or applying consistent correction models across inter- and intra-satellite interactions. The use of multi-objective optimisation will enable systematic exploration of trade-offs between different classes
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hardware with wireless communication and complex analytical software. Mussel behaviour is not binary (open/closed) but highly dynamic, with subtle patterns indicating different stressors. Training machine
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to train tomorrows leaders in earth and environmental science. For further details about the programme please see http://nercgw4plus.ac.uk/ For eligible successful applicants, the studentships comprises
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to train tomorrow’s leaders in earth and environmental science. For further details about the programme please see http://nercgw4plus.ac.uk/ For eligible successful applicants, the studentships comprises
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. Applicants will have a background in genomics/bioinformatics and be able to perform research on complex genomic datasets using the command line in High Performance Computing cluster environments. This should