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Field
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systems. Ths position requires a deep understanding of X-ray Absoprtion Spectroscopy and prior experience with methods of machine learning and artificial intelligence. A highly competitive candidate would
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related area, including meteorology, hydrometeorology, remote sensing, surface and atmospheric modeling, or related fields. Experience in machine learning techniques are highly desirable. Please see https
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microfluidics, nano-electronics, nano-biomaterials, big data, and deep learning. Applicants must hold an M.D., Ph.D., or equivalent degree and have extensive postdoctoral experience, along with a strong
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combines biomechanics, medical imaging, statistical shape modelling, deep learning and virtual crash simulation to create more realistic and equitable safety assessment tools for tomorrow’s transport systems
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 2 months ago
. Preferred Qualifications, Competencies, and Experience Programming skills (e.g., python, bash scripting, Fortran, C++ and CUDA), expertise in computational modeling (such as Deep Learning, Molecular Dynamics
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populations. Apply Artificial Intelligence (AI) methods including deep learning (DL) models and supervised and unsupervised machine learning (ML) methods for integration and for Genome-2-Phenome (G2P) and risk
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Associate/Full Professor- Plant Ecology, Evolution and Systematics- Integrative Biology, and Directo
) Minimum 5 years prior experience as an independent researcher (not including PhD or postdoctoral work) and at least 3 years prior experience teaching in a higher education environment Preferred
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vibrant community of artist-teachers and scholars who provide dynamic learning experiences for a large community of students studying the performing arts in theatre and dance. Duties and Responsibilities
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methods, risk and reliability, stochastic control processes, dynamic programing, deep reinforcement learning. Strong track record in scientific contributions supported by peer-reviewed publications. Strong
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of reproducible code by using code sharing platforms, version control, workflow languages and container solutions is a merit. Experience in training deep learning-based models on HPC-resources is also meriting. A