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The Department of Mathematics and Computer Science (IMADA) at the University of Southern Denmark, Odense, invites applications for a PhD position in algorithms. The position has a duration of 3
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We have the power of over 40,000 students and co-workers. Students who provide hope for the future. Co-workers who contribute to Linköping University meeting challenges of today. Our fundamental values rest on credibility, trust and security. By having the courage to think freely and innovate,...
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for Quantum-enhanced, distributed radar signal processing techniques that maximise target Signal-to-Noise Ratio (SNR). The algorithms we will derive will be applied and tested in the context of target detection
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. Project description This PhD project focuses on advancing the scientific computing foundations of quantum spin dynamics by developing efficient numerical algorithms for modeling complex, open quantum
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computing. This will include, but is not limited to, the design of distributed quantum algorithms, circuits, and error correction, as well as the interplay between circuit optimization and circuit
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PhD project: Modelling Resilience of Water Distribution Networks Supervised by Rasa Remenyte-Prescott (Faculty of Engineering) Aim: To develop an modelling approach for assessing water network
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-cases of classical supercomputers, the development of quantum CFD algorithms will be of widespread benefit upon the arrival of fault-tolerant quantum computing. This project involves the adaptation
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on the assimilation of Distributed Acoustic Sensing (DAS) data, using fiber optic cables deployed for the internet to estimate the state or parameters of complex spatiotemporal dynamics in urban environments within
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PhD Studentship: Distributed and Lightweight Large Language Models for Aerial 6G Spectrum Management
resources. To fill this gap, this proposal aims to design novel distributed and lightweight LLMs for spectrum management in aerial 6G networks. Specifically, the project will design wireless-aware data
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is not a standalone concept and has close connections to diversity, transparency and bias. In this position, the PhD candidate will work on algorithmic fairness in job recommender systems