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infrastructure to promote rich, systemic, automated data generation and curation. They will harness machine learning to drive unattended decisions (self-optimization and self-correction) and harness artificial
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Requirements Ability to work standing and/or sitting for multiple hours Ability to conduct computer work for multiple hours Non-Standard Work Schedule This is an Essential Personnel role: Essential Personnel
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, including Python and/or Matlab Applied data science methods, such as machine learning and AI Experience in automating laboratory equipment and processes including use of LabView PHYSICAL/MENTAL REQUIREMENTS
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learning and career advancement. We work in urban and suburban locations and collaborate with each client to understand their goal and vision. If you are looking for rewarding work on a variety of projects
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National Eye Institute, National Institutes of Health | Bethesda, Maryland | United States | 23 days ago
support clinical research activities by collaborating in the development of machine learning and AI approaches that integrate multiple modalities, advanced statistical methods, and data management
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, FBRM, UV/Vis Computational fluid dynamics (CFD) expertise in M-Star or Fluent P rograming experience , including Python and/or Matlab Applied data science methods , such as machine learning and AI
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Job Summary: The Senior Scientist Computational Biologist will be a key member of the Machine Learning and Computational Sciences Team, focusing on the analysis and interpretation of complex
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-year college or university. CERTIFICATIONS/LICENSES REQUIRED NJPE License Required or Ability to Acquire NJPE Reciprocity Essential PHYSICAL DEMANDS AND WORKING ENVIRONMENT: While performing the duties
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National Institutes of Health/National Library of Medicine | Bethesda, Maryland | United States | about 2 months ago
biostatistics, machine learning, and transcriptomics data analysis. The successful candidate with high-quality interpersonal skills will join a diverse, collegial, and cooperative group of investigators within
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technologies for novel applications. Applicants should have experience working independently in a laboratory setting, an ability to quickly learn new skills and knowledge on the job, and a broad understanding