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Computational Mechanics. Solid background in continuum mechanics and numerical modeling Strong interest in machine learning and scientific computing Experience with numerical methods for PDEs and data-driven
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training programme at the start of the PhD to develop skills in areas such as programming, data analysis, machine learning and signal processing. This will provide the technical foundation required to work
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Inria, the French national research institute for the digital sciences | Villers les Nancy, Lorraine | France | 9 days ago
dynamics data and advanced graph-based deep learning models to decode long-range communication pathways within macromolecular complexes. The PhD candidate will play a central role in this effort by
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samples, phase retrieval in this regime remains challenging, limiting multiscale imaging approaches in near-field holotomography. To address this, the PhD project combines machine learning, high-performance
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harvesting recent breakthroughs in Machine Learning (ML) and analytical modelling. Specifically, this project seeks to quantify key performance metrics and create powerful adaptive ML-driven management methods
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. The project is highly interdisciplinary and will provide training in clinical microbiology, infection epidemiology, machine learning, data harmonization, and data science. You will also participate in DDLS
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remains challenging, limiting multiscale imaging approaches in near-field holotomography. To address this, the PhD project combines machine learning, high-performance computing, and synchrotron-radiation
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for operational decision‑making, interactive design, or control‑in‑the‑loop visualisation. Machine‑learning surrogates offer speed, yet purely data‑driven models often extrapolate poorly and may violate physical
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expertise. 2. Curriculum Vitae including a list of publications (maximum 3 pages). Where to apply Website https://jobrxiv.org/job/phd-position-in-machine-learning-and-ecology/?utm_sourc… Requirements
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Systems at The Technical Faculty of IT and Design invites applications for PhD stipends or integrated stipends in the field of Machine Learning for Intelligent Hearing Assistance in Complex Acoustic