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(NSSD). In this role, you will conduct fundamental research into the integration of Bayesian methodologies with system dynamics modeling, advancing statistical methods and the open-source scientific
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The Materials Science Division at Argonne National Laboratory invites applications for a postdoctoral appointment focusing on the project of axion dark matter detection with magnon quantum sensing
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analytical technology (PAT) adds cost, time, and introduction of human error. This project aims to develop a novel, label-free microbial detection method, coupled with machine learning tailored for
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imaging and contribute to demonstrating focal-plane-array coherent THz detection. Your main tasks will include: Design AlGaAs metasurfaces for enhanced nonlinear THz-to-NIR conversion. Design metallic
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Postdoc in eDNA technology for early detection of forest pathogens Umea Department of Forest Bioeconomy and Technology We are seeking a motivated postdoctoral researcher to develop and apply
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coordinate individual unmanned underwater vehicles (UUVs) and entire swarms based on local information, for anomaly detection and infrastructure surveying in environments where communication is
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underwater anomaly detection Employer Aarhus University (AU) Location Aarhus, Midtjylland (DK) Salary Competitive Closing date 3 Nov 2026 View more categories View less categories Discipline
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short-horizon forecasting and patient-specific rebasing; implement data-assimilation methods (Kalman/Bayesian updating); design anomaly detection and missing-information inference logic. 40% Software
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data, Bayesian statistics, random object analysis, and optimal transport. Experience with neuroimaging data processing and analysis is a plus. The fellows will work with an interdisciplinary team
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King Abdullah University of Science and Technology | Saudi Arabia, | Saudi Arabia | about 5 hours ago
King Abdullah University of Science and Technology: Researcher Positions: Computer, Electrical and Mathematical Science and Engineering Division Location KAUST Open Date Nov 30, 2025 Description This is a unified application form for all positions in the Beyesian Deep Learning group at KAUST led...