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such as space, aviation, automotive, rail or medical; experience with data analysis and modelling tools, such as Python or MATLAB, including handling of datasets used for training, testing and validation
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for land cover mapping and multi temporal satellite data processing; familiarity with forest ecosystems is an asset. Strong programming skills (e.g. R, Python), including geospatial data processing
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mitigation approaches Familiarity with various mitigation regulations and guidelines Familiarity with computational tools such as Python You should also have good interpersonal and communication skills and
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data fusion, signal decomposition/unmixing, incremental/few-shot learning, and conformal prediction. Academic or professional proficiency in Python and its core scientific/ML frameworks: TensorFlow, JAX
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of the following paradigms would be considered a plus: C++, C#, Qt, Python, REST, TensorFlow, Docker, user interface design. Previous experience in GIS systems would be a plus. Hardware
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management standards, computer science, information engineering, or a related field is an asset. Experience with Python (pandas, numpy, Jupyter), SQL, or similar data handling tools is desirable. Diversity
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Engine development; intermediate C++ and/or intermediate Python proficiency; interest in extended reality development and machine learning applications; familiarity with version control and collaborative
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such tools critically and responsibly; proficiency in Python or other relevant programming languages. Diversity, Equity and Inclusiveness ESA is an equal opportunity employer, committed to achieving diversity
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; Programming in C, C++ and Python. Diversity, Equity and Inclusiveness ESA is an equal opportunity employer, committed to achieving diversity within the workforce and creating an inclusive working environment
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opportunities to develop your professional experience and competencies, to learn from ESA experts and to contribute to ESA activities. Technical competencies Python ML Libraries (PyTorch, TensorFlow, scikit‑learn