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bridges. Analyzing Structural Health Monitoring (SHM) data to identify damping characteristics. Conducting fatigue analysis under various environmental and loading conditions. Position Details and
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modelling knowledge, incorporate reliability/uncertainty, and/or explainable models. For more information and how to apply: https://www.jobbnorge.no/en/available-jobs/job/293458/phd-research-fellow-in-deep
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collaboration with experimental scientists. Our group develops and maintains open-source software for data analysis, including HiCognition (https://www.hicognition.com) for interactive exploration of genomics
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research group (please find further information at https://www.biologie.uni-konstanz.de/gruber ). You will be developing machine learning-based data science approaches for the analysis of Next Generation
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information about the network: https://euraxess.ec.europa.eu/jobs/401249 1. Context and Challenges Title: Physics-Informed Neural Operators (PINO) for Ultra-Fast Tomography: Toward Fundamental and Generalizable
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parametric and stochastic analysis techniques will be developed, that will certainly find wider applications in structural dynamics. We are looking for a PhD student holding a MSc degree in Civil
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the analysis of linked health registries though the development, implementation and application of methods for causal inference in time-to-event outcomes. For more information and how to apply: https
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(environmental sounds, multi-source mixtures) and identify the mechanisms enabling their analysis and interpretation. The PhD student will focus specifically on: • Setting up behavioral experiments combining
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Initial in vitro characterization of radioligands and assistance with further preclinical in vitro and in vivo experiments Analysis of experimental data and communication of results in work reports and
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University Medical Center of the Johannes Gutenberg University Mainz | Mainz, Rheinland Pfalz | Germany | 12 days ago
), is offering a fully funded PhD position in the area of statistical learning, machine learning, and survival analysis applied to large-scale proteomics and multi-omics cohort data. The PhD project