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analysis, processing, machine learning and statistical interpretation of HEP data at CERN in the ROOT project, taking advantage of hardware accelerators. Join CERN's SFT group in the Experimental Physics
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, econometrics, management/ decision sciences mathematics, statistics, computer science, physics or related fields. Your research track is consistent and shows a track record, or clear potential, for modelling
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. The student will also benefit from interdisciplinary and interinstitutional collaboration with international experts in machine learning, seismic monitoring/imaging, statistical seismology, and geomechanical
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international experts in machine learning, seismic monitoring/imaging, statistical seismology, and geomechanical modelling. Project team members include Dr. Federica Lanza (ETH Zürich), Dr. Luigi Passarelli (INGV
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English. Willingness to contribute towards an empirical project. Ability to speak and understand German and/or French.) Excellent knowledge of research methods and statistics; ideally you are familiar with
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). Proficiency in the statistical software package Stata and/or R (Python is a plus) Prior experience with data cleaning and management Fluency in German and English Excellent writing skills (in German and English
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the statistical software package Stata and/or R (Python is a plus) Prior experience with data cleaning and management Fluency in German and English Excellent writing skills (in German and English) Very good
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expertise, from software engineering and biomedical data management to statistical and bioinformatics analysis, as well as lab automation and advanced screening technologies. Embedded in this multi