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formulation, molecular-level characterization, and machine learning to develop predictive models linking chemical descriptors to adhesive properties. The work includes the development of a structured
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(thermodynamic and kinetic models etc.). Examples of suitable backgrounds: machine learning, programming, mathematics, physics. You will participate in designing the project according to the
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, differentiable augmentation tools, and realistic attack scenarios for audio watermarks. Publishing research in leading journals and conferences in speech, audio, and machine learning, and contributing
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augmentation tools, and realistic attack scenarios for audio watermarks. Publishing research in leading journals and conferences in speech, audio, and machine learning, and contributing to open-source