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the Portable Document Format (.pdf). The files must be designated with the name and surname of the candidate and must not exceed 5 MB combined. These files can be compressed in .zip format. 16.7
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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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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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substantial hurdles for storage, transmissibility, and long-term curation. This PhD project aims to address these challenges by researching and developing specialized lossless and lossy compression methods
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crystal plasticity and fracture, with bulk-scale processes like powder flow, compression, and tablet formation. The project will harness open-source software, including MercuryDPM for discrete particle
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multiphysics models to investigate aquifer-based compressed air energy storage (CAES) systems. The research will involve coupling fluid flow, heat transfer, geomechanics, and potentially reactive transport
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X-ray diffraction techniques Participation in developing dynamic compression experiments at the HED Science Instrument at European XFEL, including shock diagnostics (SOP and VISAR) Preparation of PhD
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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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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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on constrained platforms using techniques such as model compression, quantization, and hardware-aware neural network design. Investigating mechanisms that protect the integrity and reliability of deployed AI