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Field
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Intelligence & Machine Learning Develop machine learning and AI models to identify, predict and characterise genome instability patterns. Design generative and predictive computational models to infer mutational
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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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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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. 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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. 5. Familiarity with scientific machine learning and data-driven modelling.
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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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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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, 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
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or later, but no later than December 1, 2027. This is purely a research position and will have no teaching duties. However, if desired, successful candidates may have the opportunity to teach at KAIST. A