2,774 phd-studenship-in-computer-vision-and-machine-learning Postdoctoral positions in United States
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Physical Biology Lab and/or to pursue individual projects in each lab. The Project Environmental issues are currently among the most pressing facing humankind. As such, understanding how students learn about
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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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to solve biomedical problems, or a PhD in biomedical sciences with a strong interest to apply AI and machine learning approaches. With our strong commitment to translating research findings to actionable
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, biologics, and cannabis. Apply statistical and machine learning approaches (e.g., sequence analysis, latent class analysis, clustering) to examine medication use trajectories and patient subgroups
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bioinformatics, and statistical modeling to decode the complex molecular mechanisms that shape human vision. By leveraging high-dimensional data and cutting-edge computational analyses, we aim to uncover
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Range Based on Post Doctoral Experience Type of Position Temporary Position Time Status Full-Time Required Education PhD in statistics, biostatistics, epidemiology, bioinformatics, data science, computer
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, preferably lightsheet, confocal, dissecting. Ability to work both in a team environment and independently. Excellent organizational and record-keeping skills. Computer skills in both Mac and PC environments
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independently within a supportive group setting. Ensure compliance with environment, safety, health and quality program requirements Deliver ORNL’s mission by aligning behaviors, priorities, and interactions with
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 17 hours ago
from extreme weather to pandemics to cyberattacks. - Applicants must have significant computer coding skills, e.g., Python, R - Excellent written, oral, and interpersonal communication skills. Preferred
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methodologies generally, machine learning techniques, OR complexity analysis/nonlinear dynamics are particularly well-matched to the opportunity, but applicants with theoretical expertise related to compact