28 python-"https:"-"IFM"-"Washington-University-in-St" Postdoctoral positions in Netherlands
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computational science, collaborating with leading European research groups and benefiting from advanced GPU and HPC infrastructure. Where to apply Website https://www.academictransfer.com/en/jobs/359110/postdoc-2
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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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) at Wageningen University & Research. Where to apply Website https://www.academictransfer.com/en/jobs/359365/postdoc-position-genetic-varian… Requirements Specific Requirements You are a highly motivated
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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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attitudes. The successful candidate is expected to contribute to the research project while also having time for independent research. There will be a very light teaching load Where to apply Website https
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. Specifically, your research will provide critical insight for NGGM performance assessment and predictions. You are encouraged to visit the ESA website: https://www.esa.int/ Field(s) of activity/research
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, and participate in outreach activities that will be generally, but not exclusively, related to your research topics. You are encouraged to visit the ESA website: https://www.esa.int/ Field(s) of
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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