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Field
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active learning is desirable, as well as knowledge of behavioral coding programs (e.g., Datavyu) and mastering of statistical methods and programming languages (e.g., R, Python). Experience with online
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machine learning and statistics; experience with Gaussian process regression and/or probabilistic regression. Experience with normative modelling is an advantage. Proficiency in Python (and ideally C/C
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, parameterization, simulation experiments, and output analysis very good programming skills in at least one language (e. g., R, Python, C++, or Julia) a strong interest in interdisciplinary work (e. g., demonstrated
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machine learning methods in the context of biological systems Experience with programming (e.g., Python, Perl, C++, R) Well-developed collaborative skills We offer: The successful candidates will be hosted
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simulations of protoplanetary discs and planet formation in the context of core accretion paradigm. Proficient computational skills especially in Python, FORTRAN or C++. A good understanding of the chemistry of
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related field. You bring strong quantitative skills (e.g., R/Python, bioinformatics pipelines) and experience with high‑throughput sequencing and/or acoustic data analysis. You thrive in international
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technical universities in the world. With its strong research environment and close ties to industry, the school constantly scores well in rankings, currently listed as the strongest German business school
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statistical analysis and demonstrated proficiency in Python, R, and/or MATLAB Prior experience in neuroimaging data analysis, AI methods, and/or the computational modeling of psychological processes is