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- University of Amsterdam (UvA); Published 28 Nov ’25
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; Experience with deep learning frameworks and excellent programming skills (preferably Python) Excellent proficiency in English (oral and written). Flexibility regarding working on-site with the diverse project
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with writing scientific manuscripts and good academic writing skills; Excellent programming skills (preferably Python and/or C++); Excellent proficiency in English (oral and written). Flexibility
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the following list: C, C++, Python, Matlab, Mathematica. Programming skills will be used to build experiment control systems, data analysis systems, and to perform numerical simulations of experiments. This is
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. Knowledge of at least one programming language: Matlab, Python, is expected. Eager to work within a team and independently. Ability to collaborate with industry and academic researchers. Fluent in spoken and
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(preferably R or Python) and in adapting hydrological models. You have obtained knowledge in hydrological modelling and basic extreme value statistics. You are open to work in a team and to communicate with
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in programming (preferably R or Python) and in the processing and analysis of data sets, preferably with the focus on hydrological processes. You have obtained knowledge in statistics, especially in
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experience in pytorch and/or tensorflow) knowledge of statistical methods and programming (R and Python) prior experience in machine learning and ideally also on applications in the health domain and/or
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techniques such as magnetic imaging, optical microscopy, (FIB-)SEM analysis, or microCT. Some experience with scientific programming (e.g., Python) and willingness to further develop these skills. Strong
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economics or Urban Geography with proven quantitative research skills; proven experience with quantitative spatial analysis tools such as QGIS and extensive coding experience in preferably R or Python; strong
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; Strong experience in programming, e.g. Python, MATLAB, cluster compute Strong grasp of the English language; Eager to collaborate and to publish high-impact papers. Candidates with double or mixed degrees