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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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are expected to have experience with data analysis in a clinical context, as well as programming skills in R or Python and familiarity with command-line tools. Experience with data management and the
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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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research questions, and be able to think critically and develop your own scientific ideas. Previous experience with statistical analysis, programming (e.g., R or Python), machine learning, or genomic data
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wireless communications and/or wireless IoT systems. Strong programming skills, preferably in Python, MATLAB, C/C++ Experience with machine learning and the ability to develop, train, and evaluate data
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Assistant Professor in statistics for the development of privacy-enhancing techniques in health care
statistical modelling Strong programming skills in one of the main languages (e.g., R or Python) Proficient in English It will be considered an advantage if the candidate has experience with one or more of the
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of bioacoustic signals. Extensive experience with programming (Matlab, R, Python) including GPU programming is required, and familiarity with edge-based machine learning (particularly sound event detection), open
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one language used for computational modelling and data analysis, such as Python, R, Julia, MATLAB, NetLogo, or C++. Preferably, you have demonstrated experience with data-driven computational modelling