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research, reflected in publications or other research outputs. Strong programming skills in Python and experience with scientific computing environments. Experience in one or more of the following areas
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interest in learning, adaptation, and dynamical systems in physical contexts Experience with analytical and\or computational modeling. Proficiency in numerical methods and coding (Python, JAX, MATLAB
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: Experience with one or more general-purpose programming languages, such as Python, and general-purpose deep learning frameworks. Experience with integrating multidisciplinary inputs. Demonstrated ability in
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processing, and user-friendly GUI-based analyses for clinical and physiological research. You will combine Python-based software development, biomedical signal processing, and FAIR data design, and contribute
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hydrodynamic coastal flow fields using SWAN, SWASH, SCHISM or a comparable model; writing python code to advect virtual macroplastic items in these flow fields using the Parcels-code.org framework; exploring
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Advanced proficiency in Python and C programming languages You should also have good interpersonal and communication skills and should be able to work in a multi-cultural environment, both independently and
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languages, for example Python, and general purpose deep learning frameworks, such as Tensorflow or PyTorch; The interest and ability to share knowledge with other ESA organisational units. You should also
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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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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
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-have: You can independently and confidently analyze quantitative data and you can write reproducible code (for example, in R or Python). Good-to-have: You have worked with large-scale text data, natural