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Field
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strong international track record in content provenance and authenticity research spanning computer vision, watermarking, machine learning, privacy-preserving technologies and open standards. We have
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strong international track record in content provenance and authenticity research spanning computer vision, watermarking, machine learning, privacy-preserving technologies and open standards. We have
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Engineering, or related field. At least 3 years of relevant experience in computer vision, artificial intelligence, etc. Proficiency in programming languages such as C and Python Proficiency in deep learning
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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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background in geomodelling, geophysical and geotechnical investigation, geomechanical engineering, and machine learning. You will be expected to work effectively on a geophysical/geomechanical project, to
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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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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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. 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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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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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