16 phd-studenship-in-computer-vision-and-machine-learning Postdoctoral positions at Purdue University
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simulations. (5) Interacting with other team members on industry-sponsored projects involving combustion, turbulence, multiphase flow, machine learning and artificial intelligence, algorithm development and
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and great opportunity of interdisciplinary training in machine learning and functional genomics. The project combines cutting-edge computational approaches, especially state-of-the-art machine learning
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, computer applications and modeling, geosciences, satellite and drone sensing platforms, social sciences, education, and forest biology, ecology, health, and management for sustainable and equitable rural and
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discussions for other timelines are possible. Qualifications: PhD in a broadly related field (e.g., cognitive science, computer science, psychology, learning sciences, linguistics, speech-language-hearing
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machine learning tools. The project involves both hardwood and coniferous species such as white oak, black walnut and shortleaf pine. The postdoc’s work, which will include field work, laboratory and data
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to diverse expertise and resources across leading institutions. The successful candidate will join a dynamic and collaborative research team dedicated to developing cutting-edge AI, machine learning, and
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to learn new techniques and knowledge in imaging instrumentation and computational biophysics. Demonstrated ability to work in a team with interdisciplinary members, and to work independently with minimal
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the culture of the College of Liberal Arts (#ThinkBroadlyLeadBoldly). Pay band: In addition to annual salary of up to $75,000, this position provides office space, computer equipment, and $2500 in yearly
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addition to annual salary of up to $75,000, this position provides office space, computer equipment, and $2500 in yearly support for scientific conferences or professional development. A sign-on bonus will also be
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‘best-practices’ in semiconductor processing. Qualifications A successful candidate should have: M.S. or PhD in Physics, Electrical Engineering, Materials Science, or related Engineering discipline