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original thought takes form. Benefits We offer competitive salaries, pension scheme, 30 days’ leave per annum (pro-rata for part-time/fixed-term), a season ticket loan scheme and access to a comprehensive
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research programme with two main strands: (i) bioinformatics experiments to unravel the genetic basis of cardiovascular diseases and discover novel therapeutic targets, including genome-wide association
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the ‘Uppsala BioCenter’. The department undertakes fundamental research on model organisms, agricultural crops, forest trees and bioenergy crops. Our main areas of research comprise the interaction of plants
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validating EI measures and studying mechanisms of behavior change at scale. The postdoctoral associate’s primary responsibilities will include data preparation and management, advanced statistical analysis
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innovative statistical methods. The main focus will be on methods for sample size estimation and reliability for functional data. More applied projects aimed at improving the understanding of movement data may
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everything we do, in the belief that when views collide, disciplines interact, and perspectives intersect, truly original thought takes form. Benefits We offer competitive salaries, access to a generous
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University Hospital, Duke Regional Hospital, Duke Raleigh Hospital, Duke Health Integrated Practice, Duke Primary Care, Duke Home Care and Hospice, Duke Health and Wellness, and multiple affiliations. Be You
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System encompasses Duke University Hospital, Duke Regional Hospital, Duke Raleigh Hospital, Duke Health Integrated Practice, Duke Primary Care, Duke Home Care and Hospice, Duke Health and Wellness, and
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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | 21 days ago
observations by integrating information from multiple sources. While the primary advantage of the limb scattering technique is that it provides stratospheric aerosol observations globally, it relies on external
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master levels and advancing research about the integration of cutting-edge AI and machine learning as tools to enhance the analysis, interpretation, and scalability of Remote Sensing data. The successful