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Postdoc (f/m/d) Leader of Junior Research Group "WEEE-Recycling" / Completed university studies (...
-hand experience in the application of machine learning, simulation and modelling concepts in resource technology # Proven track record of interdisciplinary collaboration along the value chain of raw
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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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Experimental Laboratory (SSEL) at New York University Abu Dhabi invites applications for a Post-doctoral Researcher position. We seek an ambitious, well-trained, and collaborative scholar with a PhD in
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measurements from real projects, statistically analyse them, and conduct experiments with modern machine learning techniques and generative AI. A strong background in software engineering as well as some
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measurements are most informative and guiding where, when and how to observe next. By combining Bayesian inference, probabilistic modeling, and machine learning, the project aims to make Arctic observations more
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Profile: A Master`s degree and an excellent PhD degree in Biochemistry, Chemistry, or a related Molecular Science Proven Track Record in Machine Learning, Molecular Simulations, Chemoinformatics
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are seeking a postdoctoral research associate to lead an innovative EU-funded project at the intersection of polymer chemistry, computational modelling, and machine learning. The primary role is to develop a
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University. BSA salutes our veterans and active military members with careers that leverage the skills and unique experience they gained while serving our country, learn more at BNL | Opportunities
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with a background in these two areas will be considered, priority will be given to candidates who have prior experience with modular Lie superalgebras. Candidates must hold a PhD in mathematics or
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research team working at the intersection of machine learning, algorithmic fairness, human-computer interaction, and responsible AI. The project aims to investigate how bias emerges in data pipelines and AI