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: PhD or equivalent degree in Robotics, Computer Science, Machine Learning, AI, Control Engineering, or a related field. Excellent programming skills and experience with related tools and software. A
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partners to reduce CO2 emissions in steel production using machine learning. You can find more information here . You will work on a theoretical and an applied project on data-enhanced physical reduced order
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Pneumatic Tires, Structure-Process-Properties Relationships. As part of it, we are currently looking for a postdoc on machine learning for road characterization. How will you contribute? Do you have proven
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degree (PhD or equivalent) in computer science, data science, statistics, bioinformatics, or a related discipline A strong publication record in machine learning, computer science, bioinformatics
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qualifications include: Experience with radio interferometric observing, data processing, and imaging. Experience with modern machine learning / deep learning techniques and software packages. Experience with time
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-centred AI applications. This position is highly interdisciplinary as it supports the advancement of data visualisation, machine learning, and artificial intelligence domains. The Post-Doctoral Researcher
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Postdoctoral Research Associate in Forest Resilience, Climate Change, and Human Health in the Amazon
illnesses. The post holder will also co-supervise a PhD student who will be involved in the same project. This is a highly interdisciplinary project combining forest ecology, remote sensing, machine learning
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and implement computational techniques in processing neuroimaging including CT and MRI modalities. Demonstrated ability in big data analytics and machine learning techniques. Expert ability in
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, including but not limited to algorithms, databases, cloud computing, machine learning, operating systems and security. Jobs Summary: UM6P invites applications for post-doc, in all areas of Computer Systems. A
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-dimensional probability, concentration and functional inequalities ? Mathematical aspects of machine learning and deep neural networks ? Free Probability aspects of Quantum Information Theory. While excellent