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atmospheric and climate science, particularly on subseasonal timescales, and experience using machine learning methods. The postdoc will be advised by Dr. Marybeth Arcodia and includes collaborative efforts
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chemical exposures, type 2 diabetes, kidney disease, and cancer. The ideal candidate will be open-minded, eager to learn, and enthusiastic about engaging in our multidisciplinary research efforts. Key
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Post-doctoral Position in AI Causal models for Synchrotron Anomaly Detection H/F This post-doctoral position is part of a collaboration between LIAD (Laboratory of Artificial Intelligence and Data
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Helmholtz-Zentrum Dresden-Rossendorf - HZDR - Helmholtz Association | Dresden, Sachsen | Germany | about 19 hours ago
of translational medical physics research in hot-topic proton therapy projects. In close collaboration with colleagues from other institutions and our clinical team, you will establish biologically optimized proton
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be carried out independently or in collaboration with members of the Geosciences Department. One or more Hess Fellows may be appointed. Applicants must have or be in the process of completing a Ph.D
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Center for Gender and Performativity Develop, collaborate and organize research projects and develop one's independent research profile Contribute to secure external funding Co-organize international
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/agentic-AI frameworks leveraging reinforcement learning for complex clinical-reasoning tasks. In addition, Postdoctoral Fellows will: Collaborate with clinicians and researchers at the Montreal Neurological
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Job description: The University of Vienna is a cosmopolitan hub for more than 10,000 employees, of whom around 7,500 work in research and teaching. They want to do research and teach at a place that
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standards and acting in the best interest of our communities. We are encouraged to Be Curious about opportunities for learning, creating, discovering, and innovating, and are encouraged to learn from failure
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motion planning - Predictive collaboration with heterogeneous teaming - Multi-agent navigation in constrained environments - Data-driven and learning based control - Meta-learning for emergent behavior in