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interest in how technology shapes society). proficiency in Python, with hands-on experience in the open-source AI stack (HuggingFace, etc.). understanding that data in SSH is often messy, subjective, and
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/DEBtox, SSD, IBM, PBPK, or related quantitative approaches. Strong quantitative and programming skills (R and/or Python). Experience integrating large monitoring datasets and conducting statistical
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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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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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, Quantitative Genetics, Population or Statistical Genetics). Demonstrated experience in analytical and quantitative skills. Proficiency in programming and data analysis tools (e.g. Python, R, Fortran, Linux
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, sediment transport/deposition, landscape change); You enjoy working with large datasets and applying statistical analysis and modelling approaches; You use scripting/programming in your research (e.g. Python
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flows, or reinforcement learning-based design optimization. Strong programming skills in Python with experience in PyTorch, JAX, or equivalent deep learning frameworks. Ability to work independently
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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