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researcher who enjoys developing methods for complex biological data and working closely with experimental scientists. You meet the following criteria: a PhD, or a PhD close to completion, in machine learning
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and spatial analysis techniques to large-scale spatial transcriptomics and imaging datasets, using tools such as MuSpAn to identify spatial biomarkers and uncover the biological mechanisms driving
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 21 hours ago
and policymakers as an expert involving complex data and methods. Additionally, the ability and willingness to work with a large mix of people and work styles is critical. There are ample opportunities
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of density models that span the entire North Atlantic basin, addressing the problems of disparate survey data, geographically-differing species-habitat relationships, and large unsurveyed expanses that require
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to submitting your application, please review and update (if necessary) the information in your candidate profile as it will transfer to your application. Job Title: Post Doctoral Scholar Department: Engineering
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spatial transcriptomic data. A demonstrated interest in data visualization and large-scale data analysis is highly desirable. The ideal candidate will have a keen interest in understanding complex
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to manage, organize, and back up large amounts of image and tabular data generated by program and collaborator labs. Other Requirements: -May have to work on the weekend and/or after normal hours. -Travel is
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Patient Advisory Groups (PAGs), conducting qualitative interviews, running focus groups, designing and executing large-scale international surveys with quantitative data analysis, and collaborating
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FTE role supporting the international FEVER II study. C-GULL is a large contemporary birth cohort following up to 3-4,000 infants. Nested within C-GULL, HBHF is investigating early predictors of anxiety
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for this position have a great interest and knowledge in data analysis, filtering and modeling based on large amounts of data. It is important that you have a solid understanding of mining and mining systems to also