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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 2 hours ago
-oriented interprofessional education to ensure a highly skilled workforce. Research: We develop and support a rich array of outstanding health sciences research programs, centers and resources. We provide
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InLife Institute of Animal Reproduction and Food Research, Polish Academy of Sciences | Poland | 13 days ago
sciences » Other Researcher Profile Recognised Researcher (R2) Positions PhD Positions Application Deadline 12 Oct 2026 - 23:59 (Europe/Warsaw) Country Poland Type of Contract Temporary Job Status Full-time
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an exceptional opportunity to join a collaborative, multidisciplinary research program dedicated to advancing next-generation malaria vaccines while providing outstanding scientific mentorship and career
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information including Clery crime statistics for the previous three calendar years and policies, procedures, and programs the University uses to keep students and employees safe, including how to report crimes
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, statistical analyses (including multivariate approaches), and scientific writing. Mandatory requirements: PhD in physiology, ecology, neuroendocrinology, molecular biology, or related fields. Strong experience
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initiatives, including framework development, physics and statistical analysis, scholarly publications, conference presentations, student mentorship, and outreach activities. Opportunities to Contribute
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) Application Deadline 2 Oct 2026 - 21:59 (UTC) Country Sweden Type of Contract Temporary Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the
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educational programs, we are now seeking a postdoctoral researcher to work on privacy for data-driven models and high-dimensional data. The position is full-time for two years, starting on 12th January 2026
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, cell culture, and microbiological assays. Plan, conduct, and analyze scientific experiments, including statistical evaluation of experimental data. Contribute to the preparation of scientific
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development of clinical risk prediction tools. You should be confident working with large and complex datasets, using statistical programming languages such as R, Python, Stata or SAS, and have a strong