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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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, creative start-ups, big data, big ambitions, hands-on learning, and a whole lot of robots, CMU doesn't imagine the future, we invent it. If you're passionate about joining a community that challenges the
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are multidisciplinary and built on close collaborations with business and industry. This approach is further strengthened by our world-renowned Problem-Based Learning (PBL) teaching model, which is grounded in solving
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superconducting transmon qubits and electron-on-neon qubits. Characterize quantum devices using a millikelvin dilution refrigerator. Collaborate with team members and external partners to conduct quantum computing
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multimodal deep learning models combining CT imaging and clinical data, trained on the unique RADAR consortium database . These models will be validated in close collaboration with clinical and industrial
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analytics into the future of infrastructure and technology megaprojects. The appointee will conduct original research, publish in top-tier journals, collaborate with academic and industry partners, and
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About us: We are seeking experts in medical image deep learning to join our team and help develop novel computationally efficient segmentation algorithms. We welcome application from individual with
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transferable skills to address future challenges. We collaborate with industry in our education, providing them with a talented workforce and benefiting from our collaborative research endeavours. Our
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contributions. Ability to provide advice, support and supervise Higher Degree by Research students. Experience in collaborating locally and nationally in the interest of enhancing research outcomes. Ability
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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