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scientific programming using Python and MATLAB, including experience with machine learning and data science libraries such as PyTorch, MONAI, TensorFlow, Scikit-learn, and related tools for 3D medical image
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, both over the wireless interface and within the core network, will be driven by AI and machine-learning applications. This research will develop efficient communication strategies to support
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inference, and Machine Learning methods. In addition to leading their own research projects, the appointed candidate will have the opportunity to contribute to the projects of PhD students in the group, as
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the use of large language models to support neural network design and data preprocessing. The position involves close collaboration with experts in cardiovascular simulation and Scientific Machine Learning
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composites for enhanced durability, performing microstructural analysis and mechanical testing. Topology Optimization & AI Integration: Use AI and machine learning to guide structural and topology optimization
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projects. Develops research plans and budgets, designs and implements statistical, machine-learning, and bioinformatic methodologies, and manages project workflows while ensuring all sponsor requirements and
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developing new machine learning methodologies that tackle unique computational problems in healthcare applications. We use large real-world complex datasets, including data extracted from electronic health
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: 10.1101/2025.09.08.674950), and AI/machine learning. We work closely with clinicians to translate our findings into clinical practice, focusing on genomically complex sarcomas and haematological
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are encouraged to visit the ESA website: http://www.esa.int Field(s) of activity for the internship Topic of the internship: Artificial Intelligence / Machine Learning for ECSS space standards requirements
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simulation methods and quantum theoretical calculations in principle can address this but have hitherto struggled with tackling such challenging systems. With the emergence of machine learning methods in