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at the interface of biostatistics, machine learning, and biomedical data science. This mentored postdoctoral position is designed to support the development of an independent research trajectory in methodological
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for the analysis of hyperspectral imaging data applied to pictorial layers, based on coupling physical radiative transfer models (two-flux and four-flux approaches) with machine learning methods. The researcher will
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of the distinguished Association of American Universities. Connections working at New York University More Jobs from This Employer https://main.hercjobs.org/jobs/22153489/postdoctoral-associate-x28-kostinski-x29 Return
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: Prior experience running behavioral experiments is desirable, as is previous collaboration or engagement with researchers in economics. Familiarity with methods from machine learning will be a plus. All
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opportunities for methodological and/or software development, as well as the integration of machine learning into the project, depending on the candidate’s interests. This position is one of three Postdoctoral
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: Applied mathematics; Machine Learning; Mathematical Modelling Appl Deadline: 2026/03/24 10:59 PM UnitedKingdomTime (posted 2026/03/18 04:00 AM UnitedKingdomTime, listed until 2026/04/01 04:59 AM
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, Machine Learning , Neutrino , Neutrino physics and Astrophysics , Phenomenology , Quantum Field Theory , Theoretical Particle Physics , theory , Lattice QCD Appl Deadline: 2025/12/02 04:59 AM
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, land-use change, and environmental dynamics. • Design and implement spatial analytics and geospatial modeling approaches to analyze urban environmental processes. • Apply machine learning and
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projects within the CUS related to urban sustainability, environmental monitoring, and urban resilience. Key Duties • Design and implement machine learning and deep learning models for hydrological
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research backgrounds in game theory, mechanism design, artificial intelligence, machine learning, and optimization, broadly defined. Applicants working at the intersection of these areas, especially those