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- experience in programming (e.g. Matlab and/or Python) - experience in fieldwork - proficiency in scientific writing - skills in communicating with people who have different backgrounds Your workplace
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for the project. Have documented programming experience in R, Python or other common programming languages. Have experience of quantitative analysis, computational modelling, bioinformatics, machine learning
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which must be in advanced courses in one of these areas. Alternatively, you have gained essentially corresponding knowledge in another way. Experience with programming (e.g., Python, MATLAB, C/C
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methodological skills using, for example R or Python. - Strong collaborative skills and ability to take initiative. For further information about specific doctoral education, see, Study plans for doctoral studies
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robustness, fairness, and accessibility. You will design and run reproducible experiments, measure relevant resource metrics, implement prototypes in Python, and communicate results through publications and
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in one of these areas. Alternatively, you have gained essentially corresponding knowledge in another way. Experience with programming (e.g., Python, MATLAB, C/C++ or similar) and an interest in
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of machine learning such as robustness, fairness, and accessibility. You will design and run reproducible experiments, measure relevant resource metrics, implement prototypes in Python, and communicate results
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develop federated methods which can handle heterogeneous and inconsistent medical data. This involves harmonization of data from different hospitals (without having all data in one place), developing new
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courses in one of these areas. Alternatively, you have gained essentially corresponding knowledge in another way. Experience with programming (e.g., Python, MATLAB, C/C++ or similar) and an interest in
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at estimating and optimizing complexity of algorithms. Experience in telecommunications and experience of programming in Python are desirable. The applicant should furthermore have a strong drive towards solving