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project aims to address the current limitations of traditional frame-based sensors and associated processing pipelines with a new family of algorithmic architectures that mimic more closely the behaviours
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, including how to guarantee the properties of stability and constraint satisfaction while probing the system and learning a new model. This project aims to develop novel algorithms for the adaptive distributed
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model checkers; proofs of safety and/or security properties; programming languages and/or type systems; concurrent and/or distributed algorithms; and related topics. The successful applicant will work in
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optimisation algorithms to dynamically reconfigure the substation/distribution network settings to enhance the system efficiency. The optimisation algorithms will incorporate the uncertainties associated with
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Predictive and optimization-based control of smart grids: theory and algorithms School of Electrical and Electronic Engineering PhD Research Project Self Funded Dr P Trodden Application Deadline
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We are recruiting an Artist in Residence to undertake artistic research with a focus on Distributed Acoustic Sensing (DAS) technology, in the context of the recently awarded UKRI grant ‘SOUNDSCALE
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proficiency in distributed and high-performance machine learning algorithms, methods for exploiting modern system architectures for high-performance AI, and quantum distributed computing. A proven track record
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enable the development and operation of new algorithms and software to solve leading-edge research problems. You will find this work exciting if you: Want to help build and maintain some of the largest
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representation, knowledge engineering, linked data. About the role The successful candidate will join the Distributed AI (DAI) group in the Department of Informatics, King’s College London. They will carry out
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distributed tasks such as inspection of a big geographic area for fires is an important objective of this project. The project aims are to: 1) provide methodological contributions towards intelligent sensing