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team. Strong computational, quantitative, and/or engineering skills, with proficiency in developing custom code (Matlab, Python, etc.) for data analysis. Past medical research is not required, but
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research Strong mathematics background for optimization and analytical modelling of complex systems Programming languages including C++/Python and script languages For informal queries please contact
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areas in credible journals and conferences Knowledge and relevant project experience with the modelling of urban water systems Experience with Python for advanced programming, both design and planning, as
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and commercial tools (e.g. XCMS, MZmine, Compound Discoverer, GNPS, SIRIUS, etc). Proficiency in one or more programming languages (e.g. R, Python). Experience with continuous integration and best
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experience using Python machine learning and large language models. Experience in machine learning and NLP for automated misinformation detection, social media data scraping and analysis, and human annotation
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learning and scientific profile relevant to the project described above. Proficiency in scientific programming (Python) and deep learning frameworks. Fluent oral and written communication skills in English
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open source geospatial packages under OSGeo; Experience in programming with multiple languages (e.g. Java, C/C++, Python) for geospatial information systems, agro-informatic applications, crop modeling
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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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thinking, and qualitative/quantitative research methods Documented programming experience for example GitHub project on Python, Julia, JavaScript and cloud computing platforms Possesses a strong academic