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https://bioresource.nihr.ac.uk . About the job: The Senior Data Manager will lead all aspects of Data Management activities to ensure data is available to researchers worldwide and fit for analysis. By
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large datasets not publicly released, and the opportunity to work closesly with senior researchers. We seek self-driven, creative thinkers with strong quantitative skills to assist with analysis, data
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://jobs.uic.edu and upload a cover letter, resume and contact information for three references by the close date. Candidates must apply for this role by visiting the following link: https://uic.csod.com/ux/ats
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. You will organise large and diverse datasets and model outputs from DRIVERS and other projects, ensuring they are findable, accessible, interoperable, and reusable (FAIR). Data may include epidemiology
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/Administrative Internal Number: 25647 RESEARCH SCIENTIST 1, Computer Science and Artificial Intelligence Lab, will lead computational analyses of large-scale single-cell and spatial multi-omic datasets derived
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. Computational methods and artificial intelligence applied to large-scale molecular data are transforming the study of biological systems at all levels, from molecular structures and cellular processes to human
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, disability, age, genetic information, veteran status, marital status, and/or political affiliation in its programs, activities, or employment. See https://go.unl.edu/nondiscrimination Minimum Required
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http://www.unifi.it Requirements Additional Information Eligibility criteria Master’s degree in Computer Engineering or Master’s degree in Artificial Intelligence Eligible destination country/ies
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facility. Good understanding of how pre-analytical and laboratory methods can affect data quality. Quality control and analysis of large-scale proteomics data. Experience working in an accredited environment
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Massachusetts Institute of Technology | Cambridge, Massachusetts | United States | about 22 hours ago
Posting Description RESEARCH SCIENTIST 1, Computer Science and Artificial Intelligence Lab, will lead computational analyses of large-scale single-cell and spatial multi-omic datasets derived from