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perception, optimization, or control will be an advantage. The candidate should be comfortable with scientific programming, for example in Python and common machine-learning frameworks such as PyTorch
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Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung | Sylt Ost, Schleswig Holstein | Germany | 17 days ago
with quantitative data analysis using R, Python, MATLAB or comparable software; GIS experience is advantageous Very good command of English (approximately equivalent to CEFR level C1); knowledge
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, computational biology, statistics or a closely related field. You have strong programming skills, preferably in Python, and experience with machine learning or deep learning. Experience in computer vision
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their main activity (work, studies) in Belgium for more than 12 months in the 36 months immediately before the recruitment date. Required skills: •Strong programming skills in Python, and experience with
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)medical or nutritional sciences.Preferably you have experience with working with large datasets in statistical software packages such as R, Python or SPSS. Proficiency in English at C1 level or higher (CEFR
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with experience applying these models to practical applications for real-world challenges. Good programming skills, Python is mandatory, other languages (e.g., Java, C++) will be considered a plus to
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, longitudinal modelling, machine learning and multivariate approaches. Proficiency in programming (e.g., MATLAB, Python, or R), handling large datasets, and working with complex analysis 2 pipelines is an
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PhD in Advanced Testing, Modelling, and Simulation of Composite Materials under High Velocity Impact
work. Some experience in modelling of composite materials. Some experience in programming (Python, Fortran, CUDA or similar). Some experience in fluid mechanics and biomechanics. Personal characteristics
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learning, computing, data science, biomedical engineering, or a related field at the level of a master degree Programming skills (Python) and experience with common machine learning platforms Experience with
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deep generative models (VAEs, GANs, diffusion models) or probabilistic modelling is a strong plus. You have good programming skills in Python and experience with a deep learning framework such as PyTorch