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forward to receiving your application! Your work assignments This PhD position focuses on methodological and computational development in cryo-electron microscopy (cryo-EM), with emphasis on image
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twins, human-centric systems, robotics PhD-E: Optimizing Images Quality and Deep Learning Methods for Vineyard Disease Detection. PhD grantors: University Padova (IT) & Poznan University of Technology (PL
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Autónoma de Madrid, and funded by the Community of Madrid. Among the tasks to perform are: Management and preprocessing of audio databases. Design, implementation, and testing of deep learning algorithms
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within SCI and across other departments within Pitt, and initiatives like the $11.6M Western Pennsylvania Quantum Information Core (https://www.pitt.edu/pittwire/features-articles/pitt-investment-pa
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Saelens team. Research Project In this research project you will develop probabilistic deep-learning models that automatically extract biological and statistical knowledge from in vivo perturbational omics
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Saelens team. Research Project In this research project you will develop probabilistic deep-learning models that automatically extract biological and statistical knowledge from in vivo perturbational omics
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problems, statistical learning and machine learning (machine learning, deep learning) - Knowledge of associated software development tools and environments: Python, PyTorch, Scikit-learn, Jax, Julia
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include the development of finite elements methods, as well as inverse design strategies based on deep-learning and Neural Networks approaches. The latter will then bring the project to the experimental
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artificial intelligence (i.e. machine, deep and reinforcement learning…) to optimize efficiency, improve safety, reduce costs and promote sustainability. Collaborate with multidisciplinary teams to uncover a
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, engineering, physics, biophysics, applied mathematics, computational biology or a related quantitative field Strong background in deep learning for image analysis / computer vision, ideally on microscopy time