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statistics or machine learning is a plus. Equipment Utilized Physical Demands and Work Environment PHYSICAL DEMANDS: Standing, sitting, walking, talking and hearing. No special vision requirements. Lifting up
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, the research group has a strong program in the synthesis and application of chemical probes in complex biological systems, with an emphasis on measuring probe labeling and phenotype-driven cell selection using
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. Certifications/Licenses Required Knowledge, Skills, and Abilities JOB REQUIREMENTS: Effective oral and communication skills. Must be computer literate with proficiency and working knowledge of database and
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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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The Institute for Complex Social Dynamics (ICSD) and the Machine Learning Department at Carnegie Mellon University are seeking a talented and motivated postdoctoral researcher for a joint position
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: 270953868 DePaul University Post Doctoral Researcher NSF SCHOLAR Loop Campus (On-site) Job Description The Highlights: The Medical Informatics Lab at DePaul University's School of Computing is seeking a
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of biomechanics and computer vision to document the wingbeat frequencies and phototactic behaviors of diverse insects under diverse contexts. Candidates will be expected to plan and lead behavioral experiments
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 2 months ago
: * Introductory proficiency in Python, R, or another programming language * Prior exposure to machine learning or AI techniques in clinical research * Experience using deep learning frameworks * Familiarity with
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, molecular biology, and/or computational analyses. The postdoc will have the opportunity to guide the research of an undergraduate research assistant, if desired. Mentorship is a core mission of the Oldenburg
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advanced statistical techniques, computational modeling, network analysis, and machine learning to identify patterns and mechanisms linked to the onset and progression of mental health conditions