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physics-informed and physics-ML hybrid approaches that integrate domain knowledge with data-driven methods to advance hydrological process understanding and prediction. Conduct multimodal, multiscale data
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more effective screening and therapy. The postholder will focus on developing and applying advanced computer vision and machine learning methods for multimodal imaging and real-time analysis in
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multidisciplinary NUMERIQ project (ANR JCJC) aimed at developing fast and reliable methods in molecular simulations, with a focus on electronic structure simulations in quantum chemistry. Link to the detailed offer
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methods for image classification including machine learning and deep learning. You will develop clear workflows that allow for regular update of the derived models and maps. Furthermore, you will work
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innovative methods for processing and analyzing 7Tesla MRI images of different modalities and formats (NIFTI, DICOM, etc.) using machine learning and artificial intelligence techniques. These methods will be
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equipment. This position involves both technical and research support responsibilities. The successful candidate will contribute to method development, target and non-target analysis of environmental
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equipment. This position involves both technical and research support responsibilities. The successful candidate will contribute to method development, target and non-target analysis of environmental
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for this position will work as a member of an interdisciplinary team on research involving the use of statistical and machine learning methods for the development of Immune Digital Twins. There will be potential
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on estimated movements using eDCCs. The research will focus on data simulated using the Monte Carlo method and real data from clinical SPECT scanners with a parallel collimator, such as those available at LUMEN
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osteointegration. This will involve surface modification of implants through methods such as plasma treatment, silanization, and the application of specialty coatings to impart corrosion resistance. Additionally