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. Using a small number of representative test cases, we will trial Machine Learning-based predictive methods to estimate material condition and indicative reuse potential. The work will clarify data
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big-data lake ecology research using techniques from statistics and computer science (e.g., statistical modeling, machine learning, data mining). Knowledge of open science tools (e.g., Github, Zenodo
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 20 hours ago
characteristics, drug efficacy, and safety profiles, and how these relationships can be predicted using machine learning based on drug-specific information, patient demographics, and clinical trial data. 2
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Systems, and Mathematical Medicine & Biology, as well as interdisciplinary research in Scientific Machine Learning and Data Science. Candidates should indicate in their cover letter the name(s) of
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scientific writing skills supported by peer-reviewed publications. Experience in, or willingness to learn data-driven approaches, including artificial intelligence (AI) and machine learning (ML) models, to
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Type IIP supernovae. We use data from current (ZTF, HST, JWST) and next-generation telescopes/surveys (LSST, WFIRST) to address scientific questions using machine learning and statistical methodology
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structure of withdrawal, (2) acquire data from genetically diverse mice under a multitude of conditions, and (3) develop multimodal machine learning models and methods to determine signatures and
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King Abdullah University of Science and Technology | Saudi Arabia, | Saudi Arabia | about 24 hours ago
+ nationalities) Qualifications Core Requirements PhD in Computer Vision, Medical Imaging, Applied Machine Learning, or a closely related field. Hands-on experience with generative models — diffusion (DDPM/LDM
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Mathjobs.org | 29 days ago
focuses primarily on geometric analysis, spectral geometry, and differential geometry on singular spaces, preferably with connections to Finsler geometry, discrete geometry, or machine learning. Your
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focuses primarily on geometric analysis, spectral geometry, and differential geometry on singular spaces, preferably with connections to Finsler geometry, discrete geometry, or machine learning. Your