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, generative resynthesis attacks, adversarial attacks, and realistic downstream processing such as mixing. Publishing research in leading journals and conferences in speech, audio, and machine learning
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Chemistry and Materials Science is looking for: A Doctoral Researcher (PhD student) in Machine Learning for Electron–Phonon Interactions and Wannier-Based Hamiltonians The ELPH-ML project, led by Dr
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., 1H/13C/ 2D NMR, AFM, DLS, GPC, FTIR, zeta potential) with molecular modeling and machine learning Collaborate with international academic and industrial partners Who we’re looking for A curious
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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
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. A strong background in energy-system modelling, mathematical optimization, machine learning, reinforcement learning, or data-driven decision-making is appreciated. Experience with programming and
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Fire Dynamics Simulator CFD code Experimental validation of simulations Machine learning for accelerated evaluation of radiative properties The doctoral degree will be awarded upon successful
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quantum algorithms and their optimization, adiabatic quantum computation, and quantum machine learning. Theoretical and applied research into the capabilities of quantum computing and quantum
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computation, and quantum machine learning. Theoretical and applied research into the capabilities of quantum computing and quantum advantage is a prospective topic across four application domains
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Laboratory and field-based structural testing and data acquisition Direct and indirect sensing methods for bridges, including remote sensing techniques Machine learning and artificial intelligence for
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optimization, adiabatic quantum computation, and quantum machine learning. Theoretical and applied research into the capabilities of quantum computing and quantum advantage is a key focus across four application