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The University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 19 days ago
projects are the analysis of gene expression patterns in malignant human tumor samples mostly coming from clinical trials and preclinical model systems, and on the continued development of genomic-based
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. Furthermore, a novel predictive algorithm of School-age neuropsychological outcome will be developed combining radiomic model of brain development, with qualitative neonatal MRI findings. Achievement
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://www.yantlab.net/ ) Using large-scale graph-based pangenomics and forward evolutionary simulations, the student will develop predictive models of polyploid genome evolution across contrasting timescales. The student
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2030 program (see https://www.pepr-risques.fr/fr/programme-de-recherche-risques-irima ). IRIMA is led by CNRS, Grenoble Alpes University and BRGM, and aims to structure and strengthen hazard and risk
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to better understand and characterize variability of water at the land surface - i.e. in soils, snow and groundwater - to help in predictions of future water availability, global water cycle dynamics and sea
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Modeling Core is home to a consortium of postdoctoral fellows who provide modeling expertise for a wide range of projects as integral members of those research teams. Unit URL https://imci.uidaho.edu
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Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description he project aims to develop a data-driven model to
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Are you a researcher driven to understand and predict the fundamental mechanisms limiting lithium-ion battery performance? We are recruiting a Research Associate in Lithium-Ion Battery Modelling
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of the North American Ice Sheet Complex forebulge. The candidate will calculate misfit values between the statistically modeled RSL and glacial isostatic adjustment (GIA) model predictions of RSL to identify
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Architecture Search (NAS) that can automatically design efficient deep learning models optimized for specific embedded hardware platforms. These models will be deployed in resource-constrained, standalone