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security - A very good knowledge in programming (such as in C, Java or Python) - In-depth understanding of computer systems (assembly code, compilers) Additional Information Work Location(s) Number of offers
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to work independently and effectively Good command of English, good communication and team working skills Qualifications below are seen as merits Good Python programming skills, working knowledge
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of medical imaging technology and physics. Specific proficiency in relevant software and programming languages, e.g. Matlab and Python. Basis for assessment and selection In accordance with the provisions
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related field, Knowledge in fluid mechanics and heat transfer, Programming skills (Python, MATLAB or equivalent), Strong English communication skills. Experience in multiphase flows, modeling, or AI methods
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methods, and additive manufacturing is considered an advantage. You should also have programming experience, preferably in Python, and demonstrate good command of English, both spoken and written. What you
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. Strong programming skills in R and/or Python are essential, as well as prior experience in data analysis, statistics, or machine learning. The project involves large-scale single-cell and spatial
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considered a plus Understanding of Python scripting is considered a plus. As a person you are a strong communicator and are comfortable solving complex problems. This will sometimes require contacting system
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an advantage. You should also have programming experience, preferably in Python, and demonstrate good command of English, both spoken and written. What you will do Design, analyse, and test bioinspired compact
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Observation data analysis. You are fluent in Python and have solid experience with relevant machine learning and geospatial libraries such as PyTorch, TensorFlow, GDAL, rasterio, and zarr. You have experience
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. Preferred qualifications: Proven experience applying machine (deep) learning to imaging data. Strong programming skills, preferably in Python, and use of version control (Git/GitHub). Knowledge of open-source