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analysis. Proficiency with statistical software (e.g., R, Stata, or Python) and transparent, reproducible workflows. Strong collaborative skills. Excellent written and spoken English. Desirable Experience
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and/or data processing in Python. Knowledge about solid state physics. Knowledge about magnetic materials. Personal characteristics To complete a doctoral degree (PhD), it is important that you are able
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/BCR sequencing) and familiarity with R or Python are highly desired. Personal qualities: We seek a candidate who is intellectually curious, creative, resilient, meticulous in their research, and has a
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., Python, Matlab, and/or Julia), as well as a strong interest in climate science and biogeochemical cycling. Previous experience applying Bayesian inference, data assimilation, inverse modeling, and/or
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placing the results in a relevant clinical context that you have good programming skills in Python (PyTorch/TensorFlow) and are proficient in programming in Linux/shell that you are familiar with common
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one programming language, e.g. C++, Matlab, Java, Python, Julia or others PLEASE NOTE: For detailed information about what the application must contain, see paragraph “About the application
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Python) Mathematics Knowledge of these needs to be documented, and GPA (grade point average) and translation rules for the European Standardized Character System must follow the application. Moreover
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sub-sampling experience Experiences with paleogeographic modelling and the GPlates reconstruction freeware Scientific programming (e.g., Python) All candidates and projects will have to undergo a check
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research is a requirement. Demonstrated competencies and skills within programming and statistical analyses (e.g., in Python, R, or STATA) are a requirement. A Background/knowledge in media technology is a
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imperative, both orally and written. Documented experience with scientific programming (e.g. Python, Matlab, R; any history of activity on GitHub) as well as computational or statistical methods for data