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in the Nurse Anesthesiology Programs(see website: http://www.barry.edu/about/mission/ Teach anesthesia principles and basic sciences in didactic, simulation, and clinical settings and advise students
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this limitation in the use of satellite observations by make a direct use of radiance observations retrieved by satellites using machine learning without the need of radiative transfer calculations. The new model
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, machine learning, and related AI approaches, this is your chance to work at the intersection of data science, pathogen-research and immunology, tackling questions that matter for global health. The position
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The Department of Medicinal Chemistry at Rutgers University Ernest Mario School of Pharmacy is seeking a co-adjutant to help team-teach medicinal chemistry courses. Position Status Per Diem Posting Number 26FA0011
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 1 day ago
and top athletic programs, Carolina is an ideal place to teach, work and learn. One of the best college towns and best places to live in the United States, Chapel Hill has diverse social, cultural
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urban design with microclimate simulations and measurements, GIS and Digital Twin technologies, and machine learning. The work will be part of a Horizon pilot project aimed at realizing a scenario-based
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would choose to work with lecturers clustered into three broad areas: Science and Technology, Arts and Design, Civic and Community. Applicants from any field representing the Computer Sciences are welcome
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PhD (or equivalent) in Machine Learning, Computer Science/Engineering, Biomedical Engineering, or PhD or equivalent degree in population/public health and other related medical fields with AI and ML
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of scientific computing involving machine learning models for viscoelastic fluid flows. Legislation and regulations: Law Nº. 40/2004, of 18th August, in its current wording (Statutes of Scientific Research Fellow
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federated learning, AI security and privacy, quantum machine learning (QML), robotics, and/or AI-driven discovery in science and engineering (e.g., genomics, bioinformatics, drug discovery, infectious disease