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, modifying, and certification of the eCRF creation process related to clinical research to ensure quality data collection. Applies basic statistical methods, simulation models, and skilled statistical
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of University of Wroclaw. Employment in project: NCN SONATA o nr. UMO-2024/55/D/ST2/01205 – project manager dr David Osten. Requirements PhD degree in theoretical or mathematical physics, or mathematics, by
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7 Jul 2026 Job Information Organisation/Company University of Warsaw: Faculty of Mathematics, Informatics and Mechanics Research Field Computer science » Other Researcher Profile First Stage
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7 Jul 2026 Job Information Organisation/Company University of Warsaw: Faculty of Mathematics, Informatics and Mechanics Research Field Computer science » Other Researcher Profile Recognised
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for this post you should; • A PhD (or close to completion) in Statistical Genetics, Genetic Epidemiology, Computational Biology, Bioinformatics, Statistics, Computer Science, Applied Mathematics, or a
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-to-impact pathway to answer research questions related to weather-related hazards to help communities nationwide. The postdoctoral associate will apply statistical and epidemiological models to examine the
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), Mathematical-Physical Modeling for Engineering (LM-44), or Nanotechnology Engineering (LM-53)—or the corresponding *laurea specialistica* degrees in Physics (20/S), Mathematical-Physical Modeling (50/S), or
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Foundation project titled: Mathematical theory of next generation fluid-structure interactions models, at the PMF’s Department of Mathematics – 1 person. Where to apply Website https://posao.pmf.hr/opening
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» Modelling tools Researcher Profile First Stage Researcher (R1) Positions PhD Positions Application Deadline 15 Sep 2026 - 00:00 (Pacific/Saipan) Country Germany Type of Contract Temporary Job Status Full-time
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Łukasiewicz Research Network – PORT Polish Center for Technology Development | Poland | 2 months ago
. The candidate will join ongoing projects in our team and perform mathematical/computational modeling. The topics include (1) constructing deep learning-based models to predict the molecular microenvironments