72 parallel-and-distributed-computing "Computer Vision Center" research jobs in Ireland
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. Back to job search About us The researcher will join the Human-Centred Computing (HCC) group at King’s at the Department of Informatics, which provides a supportive and collaborative environment and
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develop and validate a CNS-as-a-Service concept based on modern telecommunications technologies, particularly: 5G New Radio (5G NR) IP-based software-defined networking Distributed/cloud computing
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/6G demonstrations. About the role The role will be part of a £16 million 6G CHEDDAR Hub, “Communications Hub for Empowering Distributed clouD computing Applications and Research (CHEDDAR)”, led by
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Ireland Principal Investigator, Associate Professor Erivelton Nepomuceno. Project theme: Energy-Aware Modelling and System Identification for Sustainable Computing The successful candidate will join a
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, and will be supported by a globally distributed team of Core Developers. Day-to-day communication across the team takes place via GitHub, Discord, and regular hybrid meetings. This is a part-time
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together seamlessly within a single system, CHIMES² seeks to establish secure, scalable, and energy-efficient platforms for future communication and computing, delivering enhanced performance, intelligence
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subject area, such as theoretical physics, computational physics, quantum information, quantum computing, applied mathematics, computer science or a closely related discipline. Candidates who have
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of audio and human performance research. Faculty of Science & Engineering Department of Computer Science & Information Systems Contract Type: Specific Purpose Salary Scale: €34,129 - €44,311 (maximum
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signal processing for microfluidic molecular communications: design, theory, prototype, and application (REACTION)” with description in this link, contributing to the vision of Internet of Smells. In
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following skills and experience: Essential criteria 1. PhD in computer science, AI or related area 2. Proven experience of semantic technologies such as knowledge graphs, ontologies, data