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datasets High proficiency in data analysis and statistical programming using R and/or Python. Experience working in high-performance computing (HPC) environments for large-scale analyses and with workflow
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development Qualifications PhD degree in Bioinformatics, Computational Biology, Computer Science, Mathematics, Physics, or a related field Strong experience with programming in Python, R, or similar languages
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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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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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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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, or related areas. Strong programming and numerical modelling skills using Python, MATLAB/Simulink, Julia, hardware in the loop implementation or comparable tools. Experience with one or more relevant methods
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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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energy-system modelling, mathematical optimization, control, digital twins, or related areas. Strong programming and numerical modelling skills using Python, MATLAB/Simulink, Julia, hardware in the loop
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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