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-Chem • You will be contributing to the development of machine learning models used on data from Poleno Jupiters, applying Python and machine learning. • The position will focus on implementing
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general programming tools (such as Python) is desirable. For further information about the research project, please contact Professor H.C. Kongsted: [email protected] . Information about the department is
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data. Statistical analysis using R and/or Python. Reproducible computational workflows. Scientific writing and publication. Microbiome research and host-associated microbial communities. The ideal
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contributing to open-source Python packages released alongside the methods papers, including close collaboration with the second postdoc on a shared publication pipeline. You will report to the AIMS principal
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knowledge of single-crystal X-ray diffraction (SCXRD) and in SCXRD data processing Very good oral and written proficiency in English Assessment criteria and other qualifications: Experience in the Python
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data analysis; proficiency in Python or a comparable language is expected. A publication record appropriate to career stage that demonstrates the ability to conduct and communicate independent
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unit operation and flowsheet models for chemical or energy systems. Experience with one or more process simulation and/or modelling environments (e.g. Aspen Plus/HYSYS, gPROMS, Modelica, Python/Matlab
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experimental data. • Proficiency in scientific programming and data analysis tools (e.g., Python, R, Linux/Unix environments). • Demonstrated track record of publishing scientific results in peer-reviewed
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environments. Experience with software such as R, Python, SPSS, Stata, Sawtooth, Qualtrics or similar tools will be considered an advantage. The successful candidate should have strong analytical skills, good
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environments, scripting/programming (R, Python and Bash), high-performance computing and development of reproducible analysis pipelines. Demonstrated ability to independently develop, modify and troubleshoot