2,774 phd-studenship-in-computer-vision-and-machine-learning Postdoctoral positions in United States
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to support research groups associated with Institute faculty, in areas such as: ● Machine Learning and Computer Vision ● Natural Language Processing and Data Science ● Biomedical Informatics and
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any of the following areas: Neuroscience, Pharmacology, Physiology, or Biochemistry. Computer Skills Microsoft Office Suites Supervisory Responsibilities No Required operation of university owned
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project focused on the development machine-learning powered digital twin system for the structural performance of civil engineering structures. The project is a collaboration between multiple research
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understanding of artificial intelligence applications and methodologies, such as working knowledge of generative AI tools, use of large language models, machine learning, and ethical frameworks for AI
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Station, Texas Job Type Staff Job Description Our Commitment Texas A&M University is committed to enriching the learning and working environment by promoting a culture that respects all perspectives
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computer programming in R and Python *Formal training or experience applying quantitative and spatial methods to human-environment questions *Excellent academic writing and communication skills in English
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, project management, and presentation skills Proficient with computer applications and programs associated with the position (i.e. Microsoft Office suite) Strong attention to detail and follow-up skills
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Postdoctoral Associate in the Department of Biomedical Informatics & Data Science (BIDS), Yale School of Medicine Job Description We seek full-time Postdoctoral Associates in the areas of highly
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project focused on the development machine-learning powered digital twin system for the structural performance of civil engineering structures. The project is a collaboration between multiple research
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-reviewed publications. Prior experience with biological network analysis and practical application of a variety of machine learning and computer vision techniques is preferred. The successful candidate will