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environments (preferred). You possess the ability to conduct independent research and develop novel algorithms. You have strong analytical and problem-solving skills. You have a research-oriented mindset and
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transmission of information and energy, systems theory, and computational hardware and software. ECE students are encouraged to develop synergies with disciplines outside of engineering. The candidate should
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leader Prof. Hiroaki Kikuchi, Meiji University) aims to develop innovative data privacy technologies. A post-doctoral researcher who engages in the following studies is now open. https
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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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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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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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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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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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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