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and application of novel AI, machine learning, and statistical methods for biomedical and health data. The candidate will engage in both independent and collaborative research, driving innovative
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analysis; Biomarker identification through the use of machine learning approaches; and Multi-omics data integration with genomics, transcriptomics and methylomics data. Job Description Primary Duties
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, Machine Learning , Neutrino , Neutrino physics and Astrophysics , Phenomenology , Quantum Field Theory , Theoretical Particle Physics , theory , Lattice QCD Appl Deadline: 2025/12/01 11:59PM (posted 2025
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Current Employees: If you are a current Staff, Faculty or Temporary employee at the University of Miami, please click here to log in to Workday to use the internal application process. To learn how
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Two Postdoctoral Researchers in Cell Delivery-Based Beta Cell Replacement Therapy for Type 1 Diabete
applications, often taking on an interdisciplinary character. Cutting-edge contributions to areas such as computer systems, theoretical computer science, cybersecurity, computer vision, artificial intelligence
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cognitive, clinical, genetic, and proteomic data and manages them in the data repository and computer servers. Runs existing PET/MR brain image processing pipelines on the computer servers, produces
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machine learning. The successful applicant will participate in research involving human computation, knowledge discovery, machine learning, and data science. The position will provide the opportunity
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National Aeronautics and Space Administration (NASA) | Pasadena, California | United States | about 3 hours ago
Earth observation (EO) data from NASA with state-of-the-art machine learning, we can produce a more accurate, dynamic, and actionable measure of wildfire risk. Project Goals and Objectives The primary
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in solid mechanics framework Experience in non-linear solid material response and fracture modeling Experience in machine-learning modeling for solid mechanics applications Experience in
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. CADIA provides a collaborative environment where researchers tackle challenging problems in AI, machine learning, and human-computer interaction. The center offers regular seminars, visiting researcher