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mechanisms. The project will combine experimental studies with advanced signal processing and AI techniques (compressed sensing), aiming to detect early signs of failure and enable predictive maintenance
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Experience with responsive biomaterials (mechanical, piezoelectric, dynamic compression environments) Experience with immunomodulatory systems (e.g., macrophages, PBMCs) Understanding of biomaterial–immune
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provider how to adjust their compression depth, rate, and release to improve patient outcomes. The student will have the opportunity to work with a range of engineers, doctors, and paramedics and will help
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or mechanical engineering background. Experience of experimental aerodynamics, particle image velocimetry, flow or aerodynamic measurements, compressible flow, CAD would be an advantage. As part of this role you
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We are recruiting highly motivated and enthusiastic doctoral students in the field of synthesis, characterisation and/or modelling of next generation materials for hydrogen storage and compression
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. Analysis covers preprocessing, assembly of DNA fragments into complete genomes, imputation of missing data, filtering of bad data, prediction of the meaning of the DNA in individual cells, compression
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6-24): Construction of autoencoders for compression of high-dimensional fields. Sparse identification (SINDy) or genetic programming (GEP) for derivation of explicit, interpretable control laws
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experience combined compression, tension, and shear while simultaneously undergoing severe thermal gradients. Yet most current material models and design approaches are based on simplified stress states and
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manufacturing. Your work will capture compressible gas dynamics, heat transfer, free-surface/melt behaviour, and mass transfer driven by phase change within a GPU-accelerated solver to reduce simulation
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PhD position in Adaptive Protocols for Decentralized Wireless Networks - Secure Mobile Systems Group
://doi.org/10.1109/DCOSS52077.2021.00014 [E] D. Steinmetzer, D. Wegemer, M. Schulz, J. Widmer, and M. Hollick. Compressive Millimeter-Wave Sector Selection in Off-the-Shelf IEEE 802.11ad Devices, 13th