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develop methodologies (such as acoustic emission method) detecting early signs of damage, leaks, or degradation before they become critical. We will also leverage the latest developments in machine learning
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– ideally with you on board! RESEARCH PROJECT: We are seeking a highly motivated PhD student to join our interdisciplinary research team to develop a novel biophysical modeling approach based on diffusion
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their pandemic potential and classification as bioweapons. This project aims to develop a machine learning-accelerated NMR platform for the discovery of high-affinity inhibitors targeting viral RNAPs. Building
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of molecular and biological matter using X-ray and neutron scattering. One of the research areas is the development of machine learning (ML) based approaches to efficient analysis of the vast data amounts
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expand current technology to include automated live analysis, integrating machine learning algorithms capable of interpreting the complex behavioural patterns of mussels in response to environmental stress
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Project Title: Intrinsically-aligned machine learning In a truly cross-disciplinary effort, this project, funded by the Leverhulme Trust and in collaboration with the University of Manchester, will leverage
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gravitational effects on entangled photons for shining light onto the interface of quantum physics and gravity? Can we exploit quantum photonics technology for novel quantum machine learning, quantum computing
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machine learning processing of the spectroscopic data • The optical design and development of novel custom spectroscopic sensors benefitting from freeform optics. • Integration of the in-situ
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will be based in Odense, under the primary supervision of Prof. Ricardo J. G. B. Campello , but they will be expected to also work closely with other PhD students, postdocs, and collaborators both from
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available in the research group of Research Prof. Alireza Qaiumzadeh at the Department of Physics, NTNU, Trondheim, Norway. Your immediate leader will be the Head of Department. About the project The PhD