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will focus on integrating image processing, machine learning, and deep learning techniques to improve the characterization and modeling of reservoir rocks. In the first stage, CT, NMR, and BHI images
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of Probability Theory and Stochastic Processes. Deadline: October 15, 2025 Applications should be sent through https://forms.gle/eebZAJtrzKZKoYDr7 by the deadline. Two confidential reference letters should be
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of Probability Theory and Stochastic Processes. Deadline: October 15, 2025 Applications should be sent through https://forms.gle/eebZAJtrzKZKoYDr7 by the deadline. Two confidential reference letters should be
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» OtherEducation LevelPhD or equivalent Skills/Qualifications Field of Knowledge: Computer Science / Geology / Geophysics / Electrical Engineering / Mathematics - Field of Activity: Machine Learning Additional
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models of therapeutic response using machine learning combined with Fourier-Transform Infrared Spectroscopy (FTIR) applied to blood, saliva, and tumor tissue samples. Requirements: PhD completed by
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experimentation is required. Mastery of techniques associated with imaging intracellular Ca2+ oscillations and phenotypic evaluation of organelles will be considered a plus. Experience gained in different
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-graduate and/or post-doctoral research. Sound experience in cell culture, molecular biology, fluorescence microscopy and animal experiments is required. Expertise on intracellular Ca2+ oscillations imaging
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and radar remote sensing, climate time series, and hydrological models. The work will employ machine learning and explainable AI techniques to improve flood prediction under different hydroclimatic
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position within a Research Infrastructure? No Offer Description The research proposal aims to use machine learning, including large-scale language models, to analyze large datasets of smaller Solar System
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(HR+/HER2-) and aims to develop predictive models of therapeutic response using machine learning combined with Fourier-Transform Infrared Spectroscopy (FTIR) applied to blood, saliva, and tumor tissue