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Max Planck Institute for Dynamics of Complex Technical Systems, Magdeburg | Magdeburg, Sachsen Anhalt | Germany | 3 days ago
of Biological Networks at the Max Planck Institute for Dynamics of Complex Technical Systems in Magdeburg (Germany). Our group develops computational methods and tools for analyzing and redesigning
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Arab Emirates Application Deadline 26 Nov 2025 - 00:00 (UTC) Type of Contract Permanent Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is
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collaborative links thorough our collaborative network. The researcher should have a PhD/DPhil (or be near completion) in robotics, computer vision, machine learning or a closely related field. You have an
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The SigCom research group of SnT, headed by Prof. Symeon Chatzinotas, focuses on wireless/satellite communications and networking. The research areas focus on the formulation, modeling, design, and
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of Minnesota, working with Professor Russell Funk. This position focuses on using computational methods to understand how knowledge is produced, shared, and applied across complex systems. About the Project
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6 Nov 2025 Job Information Organisation/Company NEW YORK UNIVERSITY ABU DHABI Research Field Computer science Engineering Mathematics Researcher Profile Recognised Researcher (R2) Established
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the Environment invites applications for postdoctoral researchers or more senior research positions. Successful applicants will join Princeton's Net-Zero X (NZx) initiative, which is building
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undergraduate program in the Arts, Sciences, Social Sciences, Humanities, and Engineering. NYU Abu Dhabi, NYU New York, and NYU Shanghai, form the backbone of NYU’s global network university, an interconnected
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. Evaluates machine learning training using tools such as precision-recall metrics, receiver-operating characteristics curves, and confusion matrices. Trains and evaluates neural networks for computer vision
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Information content of brain wiring', funded by the Volkswagen Foundation Pioneering Research Program 'the unknown unknown.' The basic premise is simple: The information content of artificial neuronal networks