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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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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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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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12th December 2025 Languages English English English The Department of Computer Science has a vacancy for a PhD Candidate in Algorithmic Fairness in Recommender Systems Apply for this job See
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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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Almost all radar systems currently transmit from the same location. A drastic departure from this sensing architecture is distributed radar – enacted by a coherent network of spatially distributed
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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
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at scale raises privacy and real hardware constraint concerns. This PhD will focus on those challenges by developing a distributed, privacy-preserving NILM framework, so we can move from small research