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the Interpretable Machine Learning Lab (https://users.cs.duke.edu/~cynthia/home.html ) for a scientific developer to work in collaboration with other researchers on machine learning tools that help humans make better
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The Machine Learning section of the Department of Computer Science at the Faculty of Science at the University of Copenhagen (DIKU) is offering a 2 and a half year fully-funded postdoctoral position
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area, with content covering robotics and machine learning, and excellent programming skills in Python. You should have research experience in either robotics or machine learning. You should also have
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papers with the other team members. What we are looking for: You must have a master’s degree in a relevant area, with content covering robotics and machine learning, and excellent programming skills in
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focuses on translational research at the intersection of bioelectronics, healthcare-focused nanofabrication, and emerging applications of machine learning in radiology. Our team operates within a state-of
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computational costs by orders of magnitude and enabling breakthroughs in drug design and materials science. The position bridges machine learning and molecular science, with opportunities for collaboration
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Fritz Haber Institute of the Max Planck Society, Berlin | Berlin, Berlin | Germany | about 2 hours ago
skills and experience and interest in data analysis, data science, machine learning and process automation would be an advantage. Previous experience with XAS or other synchrotron-based techniques would be
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and Environmental Studies is looking for a highly motivated and independent individual to work as a Postdoctoral Associate. This position is for a post-PhD trainee preparing for a research scientist
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-of-computing-science/ Project description and working tasks The project will develop privacy-aware machine learning (ML) models. We are interested in data-driven models for complex data, including high
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students and PhD students. Applicants will have, or be close to completing a PhD in a relevant field and possess relevant experience, in the area of probability or statistical machine learning. They will