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in Python and affinity with large geospatial datasets. Interest in interdisciplinary research at the interface of geoscience, engineering, and societal impact. Good communication skills and willingness
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and written. Further expertise that would be valuable: Python software development; Natural Language Processing. Above all, you are a quick learner, proactive and eager to make things work. Our offer
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and digitizing archival data, strong knowledge of causal inference methods, good command of R and Python. Knowledge of machine learning methods is an asset. Strong command of English; command of either
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, provided they have advanced training in methodological statistics You should have advanced programming skills in R or in other statistical software such as Python, or MATLAB. You should have a solid
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involving the analysis of omics or twin datasets. Essential qualifications include: A strong computational background, with experience in one or more programming languages (e.g. R, Python, Perl, or shell
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for hands-on experimental characterization techniques and data analysis. Skills in programming (e.g., Python, MATLAB) and simulation tools. Expertise in photonic integration is not a must, but having relevant
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skills (Python) and knowledge of deep-learning frameworks (PyTorch) are expected. A certain affinity towards turning complex concepts into real-world practice is desired. The successful candidate is
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Aerospace Engineering, Aeronautics or a comparable degree, thorough knowledge of AI/ML methods, acoustics, and air traffic management are preferred, as well as excellent programming (Python, Java, C++, …) and
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process. You should also have: Competences in the field of mechanics, fluid-dynamics, electronics as well as coding (Python) are appreciated. Diversity, Equity and Inclusiveness ESA is an equal opportunity
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R or Python). Good-to-have: You have experience working with large-scale text or visual data, or datasets related to history or culture. You tackle complex data challenges with curiosity and are