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if applicants have completed courses that cover these topics during their studies Good programming skills (for example Python, Java or JavaScript) and software engineering practices is a requirement. Familiarity
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during their studies Good programming skills (for example Python, Java or JavaScript) and software engineering practices is a requirement. Familiarity with real-world programming language specifications
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of epidemiological modelling and data analysis C2 Up-to-date knowledge of epidemiological modelling approaches C3 Knowledge of relevant programming languages for model development, for example Java, R, C++, Julia C4
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community. Requirement: PhD in computer science/ engineering or related fields. Proficiency in Python is a must. Experience with other programming languages such as Java, C/C++, or Go, and frameworks like
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. neuroimaging, time-series signals, clinical records) for predictive modelling and decision support. Proficiency in programming languages such as Python (and/or Java, C/C++), with hands-on experience using AI
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research methods (e.g., interactive Qualtrics surveys; longitudinal surveys; ESM; surveys with integrated third-party services); Familiarity with programming (e.g., Python, C++, Java); Familiarity with agent
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. Possess relevant hands-on experience in Python, Java, C++ etc. and corresponding development environments.
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; for example, a Ph.D. in social psychology with no experience in engineering or computational approaches would not be acceptable. Experience with programming (Python, Java, Javascript, PhP, and others) Training
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Open Source Geospatial software and libraries, e.g. GDAL or other open source geospatial packages under OSGeo; Experience in programming with multiple languages (e.g. Java, C/C++, Python) for geospatial
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modelling. Applicants must have good skills in programming (e.g. Python, R, Java Script) Experience (for example a master project or internship) working with snow or the cryosphere is a requirement