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learning is required; familiarity with contrastive learning, computer vision, or geospatial data is welcome Very good programming skills (Python, C++, etc.) are essential Fluent English language skills
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, you have developed a sound understanding of the use of simulation and data analysis software (e.g., ANSYS, MATLAB, and Python). Do you also have experience in developing FE models of complex systems
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Knowledge in the field of Machine Learning, including training, inference, and optimisation of transformer architectures. Knowledge in the field of ML security is desirable. Good Python skills, especially
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• Interdisciplinary applications ranging from biomechanics and geophysics to fluid and polymer models Further information can be found here: https://www.math.cit.tum.de/math/forschung/gruppen/numerical-analysis
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(or MSc with several years of working experience) in computational or natural sciences with a strong computational / quantitative focus Strong programming skills in Python or R; experience with a modern
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analysis, ideally using Python-based tools and frameworks, with familiarity in areas such as statistical modelling, machine learning, computer vision, or optimisation approaches for experimental systems
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programming skills in Python; initial experience with machine learning frameworks such as PyTorch or TensorFlow Initial practical experience from a master's thesis, study projects, internships, or open-source
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integration, and statistical analysis in R or Python. We are looking for self-motivated and broadly interested individuals with a strong sense of responsibility. Flexibility and the ability to work in a fast
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inference and econometrics is a plus · Programming skills in Python, R, or comparable languages · Strong programming skills in (iOS) app development · Excellent communication skills in English
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Knowledge in the field of Machine Learning, including training, inference, and optimisation of transformer architectures Knowledge in the field of ML security is desirable. Good Python skills, especially with