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particular emphasis on trait dimensions related to tolerance, movement, and interaction. By integrating multi-taxa field data, trait-based ecology, experiments, and advanced statistical analyses, TRACE aims
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statistical methods to large-scale medical datasets (EHR, imaging, genomics, clinical trials). Design algorithms and predictive models to advance diagnostics, medical devices, healthcare access, and
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estimation, and the detection and compensation of sensor drift and degradation. The candidate will develop data processing and modelling approaches combining signal processing, statistical analysis, and data
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. Applications by email will not be considered. Application procedure and conditions We kindly request applicants to provide their nationality for statistical purposes only, as part of our commitment to promoting
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Eberswalde University for Sustainable Development | Eberswalde, Brandenburg | Germany | about 1 month ago
also welcome candidates with good knowledge of environmental statistics and/or geographic information systems. LanguagesENGLISHLevelExcellent Additional Information Website for additional job details
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statistical modelling of high-dimensional data, e.g. penalised model selection and machine learning. Demonstrable understanding of RNAseq and gene expression analysis. Experience/skills handling and securely
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learning) to empirical data. Statistical analysis. Writing research articles for publication in peer-reviewed journals. Presenting findings at conferences and research seminars. WE REQUEST Professional
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mathematics Mathematics » Statistics Researcher Profile Established Researcher (R3) Application Deadline 22 Feb 2026 - 22:59 (UTC) Country Sweden Type of Contract To be defined Job Status Full-time Is the job
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, Environment, Science or Data Analysis, Statistics, Computer Science, Mathematics, Biology or related fields; Sense of responsibility and ability to communicate and integrate into multidisciplinary work teams
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the scientific field of the competition. c) Previous experience in statistical analysis of time series and mixed models. d) Previous experience in processing and analysing physiological data (electrodermal