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will provide PhD training to 15 Doctoral candidates (DCs). Consortium objectives: MetaTune aims to develop a new generation of reconfigurable metasurfaces that enable efficient, simple, and industry
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are not limited to: Learn research techniques to develop algorithms and models for the simulation of field data Participate in experimental activities such as research design, data collection, technical
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networks are not well-suited to the computational constraints of FHE. The project aims to develop more efficient neural network architectures tailored for encrypted computations. The postdoctoral researcher
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turbine blades. Successful re-development for end-of-life composites could enable reuse in other structural applications. This PhD will investigate the development of hierarchical Bayesian algorithms
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on methodological development in cryo-electron microscopy (cryo-EM), particularly in image reconstruction and 3D volumetric analysis of macromolecular structures. Rather than aiming to incrementally optimize existing
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will develop and evaluate fault detection and fault location algorithms for these systems. The project is funded by GE Vernova under a wider collaboration with Imperial College London. You will be co
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the Unconventional Communications and Computing Laboratory (UC2), led by Dr Michael T. Barros, which develops modelling and algorithmic methods for networked communication and computation under real-world constraints
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(E13 TV-L, 100%, starting 1 April 2026 or as agreed) 22.12.2025, Academic staff The Professorship “Algorithmic Governance and Public Policy” (Prof. Daria Gritsenko), invites applications for a
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developing prototype systems and algorithms • Experience with MRI and/or fMRI data (human data preferred) • Experience with high resolution and high field MRI and/or fMRI • Excellent verbal and written
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intelligent sensing, followed by detection of the important events.In the light of autonomous decision making, the project aims at developing machine learning algorithms for knowledge extraction from data