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constraints using multi-scale feature fusion and generative data augmentation to enhance LVLM perception capabilities; (c) optimise model efficiency: implement model distillation techniques to compress LVLMs
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, electrical & electronic engineering, or equivalent. Background knowledge in signal representation/processing, visual data compression, and data-driven and machine learning/analysis. Prior research experience
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, they must be compressed before upload. Please note that information on applicants may be published even if the applicant has requested not to be included in the official list of applicants - see Section 25
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, electrical & electronic engineering, or equivalent. Background knowledge in signal representation/processing, visual data compression, and data-driven and machine learning/analysis. Prior research experience
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will also address structural powerplant design and integration, refining computational methods to use high-fidelity aerodynamic data for accurate load prediction and system-level design decisions. About
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for Space Communications Research . The person hired will work within research on: Quantum information theory, Quantum compressive sensing, Quantum error-correcting codes, Quantum computing, and/or Post
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quantum technology, and it may also be associated with the new Center for Space Communications Research . The person hired will work within research on: Quantum information theory, Quantum compressive
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). Programming in C++ or Fortran and proficiency with MATLAB or Python scripting. Experience with tools for simulating chemical kinetic, e.g. Cantera or CHEMKIN. Background in compressible flows and applied
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. Cantera or CHEMKIN. Background in compressible flows and applied aerodynamics. Experience in data analysis and interpretation of large datasets. Knowledge and experience from use and development of CFD
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positive impact through cross-disciplinary interactions. Actively seeking new funding and creating opportunity for spinouts. Working towards real-world outcomes. Integrating large-scale data, AI, and