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Field
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scale. Increasingly, our work integrates AI and machine learning approaches to process and interpret large and complex Remote Sensing datasets. When joining our group, you will also join the wider 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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. Sparse sensing, optimization, or Bayesian experimental design. Machine learning for imaging. Synchrotron experiment experience. Semiconductor devices or metrology. We offer We offer a fully funded
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. Author scientific publications, present findings at conferences, and contribute to patents or technical innovations. Qualifications: PhD in Artificial Intelligence, Machine Learning, Data Science
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Institut d’Investigació Biomèdica de Girona Dr. Josep Trueta (IDIBGI-CERCA) | Spain | about 2 months ago
will begin from June 2026. Education and Background PhD degree in a relevant quantitative discipline such as Bioinformatics, Statistics, Mathematics, Data Engineering, or Biomedical Engineering
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technologies including semantic/task-oriented data processing, signal processing, and network resource management to improve the performance of future wireless communication systems. Finally, due to the large
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Engineering Department at The Pennsylvania State University. This position involves the development and application of numerical analysis approaches using Machine Learning based multi-physics tools
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at the atomic scale, using density functional theory-accurate machine-learned potentials and molecular dynamics simulations, in close collaboration with leading European research institutes and steel industry
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modeling, machine learning, • Experience in human electrophysiological research is a plus, experience in intracranial human research large plus, • Knowledge of cognitive system is a plus, knowledge of
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, Europe and Asia. The postholder will have opportunities to develop their academic profile in data science, machine learning and statistical genetics within a friendly, accessible and internationally