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with skills in quantitative analysis and an interest in political theory, or in applied philosophy with proficiency in quantitative data analysis, will be given priority. An interest in developing
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of machine learning and advanced molecular dynamics techniques for molecular simulations and to study Nucleic acids structures and their interactions. For more information, please visit https://nyuad.nyu.edu
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 4 hours ago
, analysis and dissemination, and project administration. https://www.cpc.unc.edu/about/ Position Summary The Carolina Population Center at the University of North Carolina at Chapel Hill invites applications
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22 Aug 2026 Job Information Organisation/Company CNRS Department Écologie Société Evolution Research Field Biological sciences Environmental science Researcher Profile Recognised Researcher (R2
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 4 hours ago
world. Position Summary This Postdoctoral Research Associate will conduct advanced research in artificial intelligence, machine learning, computer vision, and medical image analysis. The position will contribute
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for downstream research and UUV operations. Model-Data Integration, Validation, and Analysis – 15% Integrate physics-based model outputs with observational and operational environmental datasets. Evaluate model
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morphodynamic models AND/OR proficiency and experience in coastal/nearshore field data collection and analysis. Strong written, oral, and visual communication skills. Good understanding of coastal sediment
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encoded FRET biosensors for mitochondrial functionality. - Implement innovative data analysis protocols and approaches for FRET/FLIM or radiometric FRET microscopy in cultured cell lines - Modify and/or
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, ELISA, coagulation assays as well as carry out data analysis. The candidate’s research experience, technical skills, and relevance to the PI’s research will be used in determining the title and
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-world buildings, data analysis, and modeling. Candidates with complementary expertise who are interested in developing new research directions within the broader field of indoor air quality are also