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27.10.2025 Application deadline: 30.11.2025 Are you excited about the possibility to explore ethical, philosophical, legal, epistemic or social implications of using machine learning in different
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(SHORES) and the Division of Engineering, New York University Abu Dhabi, seek to recruit a Postdoctoral Associate to work on a fascinating project focused on the development machine-learning powered digital
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probabilistic machine learning and geospatial sciences. Limited teaching may be arranged, if mutually agreed, in exchange for a contract extension. Qualification Requirements Applicants must hold a PhD degree in
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to the development of the research milieu. Requirements PhD degree in a field closely related to the position (e.g., computerized image analysis/processing, machine learning, artificial intelligence, data science
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Requirements Applicants must hold a PhD degree in Machine Learning, Artificial Intelligence, Computer Science, Statistics, or a closely related field. A strong research background and programming experience
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The Department of Electronic Systems at The Technical Faculty of IT and Design invites applications for a postdoc in the field of Acoustic Sensing and Machine Learning for Sustainable Battery
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developing new machine learning methodologies that tackle unique computational problems in healthcare applications. We use large real-world complex datasets, including data extracted from electronic health
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/english/research/projects/activate/index.html The researcher will be part of a growing team of researchers, postdocs and PhD students working on intelligent observing systems using machine learning and data
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: Responsible for performing organic reactions in Dr. Sielecki’s lab within the Institute of Advancing Medical Innovation and the Department of Cancer Biology. Post-docs will learn methods appropriate
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at the intersection of AI, NLP, and industrial applications. Contribute to the development of scalable and interpretable AI tools for real-world deployment. Qualifications: A PhD in Computer Science, Machine Learning