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, including Bayesian designs, pragmatic trials, hybrid-type studies, clustered designs, de-centralized trials, and rapid cycle research to support learning health systems. Clinical trial data management
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find more information about working at the University of Potsdam at https://www.uni-potsdam.de/en/arbeiten-an-der-up/employer-up/overview For further information about this position, please contact Mr
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learning methods (e.g., predictive modelling, clustering, multivariate integration) to large-scale time series and sensor datasets. Contributing to the development of risk models and decision-support tools
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ESA Expert Support Laboratory for the SAR Mission Performance Cluster, has built advanced frameworks for SAR/InSAR processing that underpin large-scale InSAR-based ground motion services in Norway and
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tasks: You will work together with renowned astrophysicists and computer scientists in the DFG-funded “Dynaverse” Excellence Cluster You will invent, implement, and benchmark novel AI tools (reinforcement
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Information (QG&QI), Quantum Materials (QMat), and Soft Matter (SM). You will join the Strontium Quantum Gases Group of the QG&QI cluster . We are using ultracold atoms and trapped ions as a means to
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the reference number 27697, via our online portal: Apply now via https://jobs.uksh.de/job/Kiel-PhD-%28mfd%29-Statistical-Genetics-Machine-Learning-Schl-24105/1279933701/ For more information visit: www.uksh.de
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ideal candidate will have broad experience interpreting sequencing data from large cancer-related datasets and be local to the St. Louis area to facilitate in person meetings throughout the week with a
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candidate will have a PhD in a relevant biological subject, or MSc / MPhil plus significant experience in industry in the field of computer vision and machine learning. They will also have extensive research
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knowledge for a better world. You will find more information about working at NTNU and the application process here. About the position The Department of Structural Engineering has two vacancies for PhD