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version: https://repositorio.inesctec.pt/editais/pt/AE2026-0086.pdf CALL FOR GRANT APPLICATIONS (AE2026-0086) INESC TEC is now accepting grant applications to award 1 Research Grant (BI) within the scope
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spectrometry techniques available in the laboratory, as well as optimizing analytical methods if necessary; Performing advanced data processing, including statistical and multivariate approaches, and potentially
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are strongly encouraged. Candidates interested in acquiring experience with chemometrics and multivariate statistics are highly desired. Feel free to reach out to learn more about this opportunity. Keywords
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biology of infection. For more information, please see https://www.scilifelab.se/data-driven/ddls-research-school/ The future of life science is data driven. Will you be part of that change? Then join us
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Senckenberg Gesellschaft fuer Naturforschung | Wilhelmshaven, Niedersachsen | Germany | about 1 month ago
communities • Multivariate statistical analysis of community and environmental datasets • Spatial analysis and georeferencing of ecological data using GIS • Development and implementation of species
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discrete black box combinatorial optimization problems (https://arxiv.org/abs/2510.01824 ). In this work, we parameterize a multivariate autoregressive generative model for generating solutions. By sampling
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of Neurology (https://movementdisorderslab.umn.edu/ ). The postdoctoral researcher will be involved in the execution of experiments examining the effects of globus pallidus deep brain stimulation on motor and
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Master’s degree in epidemiology, data analysis and biostatistics, AND who already has experience in analysing observational cohort data (multivariate statistical analysis, clustering, large-scale database
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neuroimaging data; preprocessing and analysis of fMRI data; and the application of advanced methodologies (functional adaptation, multivariate signal analysis, and effective connectivity). The candidate will
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contribute to high-impact research on machine learning related to the analysis of IoT data in the form of multivariate time series. The DESS group is part of Department of Computer Science that belongs