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Pediatric Trauma Surgery Data Manager (Part-time) Position Summary At Stony Brook Medicine, a TH Staff Associate/Trauma Surgery Data Manager is a valuable member of our team, who will be responsible
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news engineering (Television Studio / Control Room) or multimedia production experience. Experience with photography, cameras and/or audio recorders. Experience in computer video editing and graphic
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service. Skilled with scripting using shell, Python, or other programming languages. Experience with upgrading, maintaining and troubleshooting computer hardware. Experience with web programming (i.e. HTML
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service. Skilled with scripting using shell, Python, or other programming languages. Experience with upgrading, maintaining and troubleshooting computer hardware. Experience with web programming (i.e. HTML
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multidisciplinary teams to uncover patterns, trends, and relationships in aging data. Required Qualifications: (as evidenced by an attached resume) * Ph.D. degree in Data Science, Computer Science, Bioinformatics
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, Computer Science, Bioinformatics, Biomedical Engineering, Computational Biology, Neuroscience, or a closely related field. ● 5 years of experience (strong expertise) in data analysis and machine learning
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-round expert staff, state-of-the-art laboratory, research and teaching facilities, and connections to researchers at dozens of global universities have no parallel in Madagascar. Major research facilities
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techniques. Perform epigenetic analysis through next-generation sequencing library preparation (e.g. spatial genomics and metabolomics). Perform bioinformatics analysis. Maintain mouse colony and perform eye
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techniques. Perform epigenetic analysis through next-generation sequencing library preparation (e.g. spatial genomics and metabolomics). Perform bioinformatics analysis. Maintain mouse colony and perform eye
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, Computer Science, Bioinformatics, Biomedical Engineering, Computational Biology, Neuroscience, or a closely related field. ● 5 years of experience (strong expertise) in data analysis and machine learning