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., linear algebra, statistics, optimization, and calculus) is expected, along with programming experience using deep learning frameworks in Python (e.g., PyTorch). While prior knowledge of machine learning
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, i.e. ranging from Python/Julia/Matlab to the development of parallel computing frameworks based on the PETSc library using the c++ computing language. You know and have in-depth experience within finite
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basic knowledge in glaciology or geodesy. Good expertise in programming, e.g. in Python, MATLAB, or other high-level programming languages. You must have a two-year master's degree (120 ECTS points) or a
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mechanics, or similar relevant areas. Demonstrated programming skills (e.g., MATLAB, Python) for model development and simulation. Excellent communication skills in English, both written and verbal. Mobility
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. Programming skills in Python, with experience in deep learning frameworks such as TensorFlow or PyTorch. Experience with computer vision techniques, image processing, and neural networks. Familiarity with
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achieve this, you must have prior knowledge in the following topic: Wind farm flow modelling Machine learning Python scientific programming Excellent communication skills, both in writing and oral
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from many different sources into data frames that can be analyzed with biostatistical applications in the statistical software R/Python. Performing data analysis in accordance with time-structures and
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skilled in data analysis with proven experience with programming, e.g. Python Be skilled in experimental work Previous experience with microscopy is an advantage but not required. You must have a two-year
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quantitative methods Experience in one or more programing languages (e.g. R, Python) Knowledge of public health, foodborne disease surveillance, and animal disease surveillance is an advantage Excellent
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suited for data science and statistics: Python, R, MATLAB Strong English communication skills; both written and orally Experience with any of the following is appreciated. mySQL, computational workflow