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assessment criteria Experience with programming (e.g. Python, MATLAB, Fortran or similar), numerical modelling, remote sensing, large datasets, or fieldwork is considered meritorious. Employment process
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for QMSS (including which course(s), if applicable) and the skills (e.g., analytical tools such as Excel, R, Tableau, Python, etc.) and experiences (e.g., jobs, internships, research, coursework, teaching
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to have a fluent command of written and spoken English with an extensive vocabular (at least B2 level according to the CEFR: https://go.fzj.de/languagerequirements ), ideally supported by a certificate
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programming skills, ideally in Python Experience with cloud computing environments or distributed computing platforms Experience managing container-native workflows Experience or knowledge of next generation
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which must be in advanced courses in one of these areas. Alternatively, you have gained essentially corresponding knowledge in another way. Experience with programming (e.g., Python, MATLAB, C/C
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AI applications as well as Python-based coding . Have a degree in Computer Science/Computer Engineering. Possessing a Master’s or PhD degree will definitely be advantageous. Knowledge of machine
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skills are required, particularly in Python and machine learning libraries, along with experience in data management. Experience in model deployment or the development of operational tools will be
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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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salaried and benefits eligible. Information regarding postdoctoral fellow salary, which is determined by the number of years post PhD, and benefits can be found at https://postdoc.hms.harvard.edu/guidelines
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the application which project you are specifically interested in. Further details on the projects can be found here: https://www.fz-juelich.de/en/jcns/careers/fellowships/tasso-springer-fellowship-program Your