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individuals participating in studies investigating the cardiovascular consequences of preterm birth. By combining fluid dynamics, machine learning, and advanced imaging analysis, the project seeks to develop
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will focus on efficient probabilistic analysis of high-dimensional and dynamic systems, including advanced sampling, surrogate modelling, and AI or machine-learning methods where appropriate. Key
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. Ideal candidates will have demonstrably strong research skills, evidenced by multiple publications in top-tier machine learning or artificial intelligence conferences and/or leading scientific journals
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artificial intelligence and machine learning. The postdoctoral fellow will contribute to the development of a comprehensive, multi-modal framework for predicting and managing cardiovascular disease by
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. 5. Familiarity with scientific machine learning and data-driven modelling.
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of the Max Planck Society for the Advancement of Science. The Department of Machine Learning and Systems Biology , headed by Prof. Dr. Karsten Borgwardt, invites applications for a Postdoctoral Research Fellow
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demonstrate experience in animal behaviour research, ideally in aquatic species, together with practical skills in video-based behavioural analysis and/or applying computer vision or machine learning methods
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to evolutionary time scales. One of the goals of the SCINet Initiative is to develop and apply new technologies, including AI and machine learning (ML), to help solve complex agricultural problems that also depend
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research in formal verification, machine learning and artificial intelligence system assurance. The successful candidate will develop new techniques and tools for analysing, verifying and improving
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, clinical and sensor data processing, quantitative image analysis and machine learning. They will establish and maintain robust research databases and FAIR-compliant data management processes for large, multi