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forward allele-frequency diffusion and backward genealogical merging processes. The PhD candidate will work at the interface of machine learning, statistics, probability, and with applications in
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meters. These instruments produce large amounts of data that require several processing steps before the relevant physical variables are obtained. Typically, machine learning methods are used to optimize
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an appropriate discipline. Ideal candidate will have some prior knowledge in deep learning and computer graphics. Subject Area Medical imaging, biomedical engineering, computer science & IT
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IT4Innovations National Supercomputing Center, VSB - Technical University of Ostrava | Czech | about 1 month ago
operates the first Czech quantum computer named VLQ. For more details, see www.it4i.eu . Activity description: · conduct research in machine learning with emphasis on computer vision, · develop and evaluate
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is looking for an aspiring PhD candidate to research causal machine learning and uncertainty quantification for Earth Observation time-series. Currently, predictive AI in Earth Sciences relies heavily
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· Develop and apply transformer-based foundation models and machine learning methods for large-scale epigenetic datasets · Integrate longitudinal data and biological prior knowledge into AI models · Actively
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science/biomedical engineering or of relevant scientific field A solid background in machine learning Extensive experience with either computer vision or image analysis Good knowledge of deep learning
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into the sample of interest. Recently we have been using AI and machine learning to predict the distortion present and significantly speed up this correction process. This PhD project will take the latest in AI
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Inria, the French national research institute for the digital sciences | Palaiseau, le de France | France | about 1 month ago
in particular computer vision. Particular topics of interest include visual comprehension, hyperspectral imaging, numerical and parallel optimization, and unsupervised learning. A particular emphasis
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, or research assistant job) - Solid experience in machine learning and AI (essential) - Experience with imaging data analysis - A collaborative approach to doing science and willingness to help other lab members