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should have a strong quantitative background, for example in statistics, mathematics, computer science, or a related field, very good programming skills, a demonstrated interest in statistical modelling
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personal qualities and individual suitability. Experience in kinematics, dynamics, programming, safety and CAD modelling is considered an asset. Knowledge of AI-assisted automation is particularly
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necessary. Proficiency in Python programming, particularly with Python libraries such as Spectral Python (spectral), NumPy, SciPy, and OpenCV and familiarity with at least one engineering design software
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proven advanced experimental capabilities and excellent programming skills (e.g. C++, ROS, Matlab, etc.). You should have a strong vision to evaluate and demonstrate the research findings in real life
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absence. The research tasks require a solid mathematical background with proven advanced experimental capabilities and excellent programming skills (e.g. C++, ROS, Matlab, etc.). You should have a
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statistical programming in R or Python is desirable but not required. The application should include a brief description of your research interests and relevant experience, a CV, copies of degree
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or machine learning, modelling and simulation, experimental robotics, and scientific programming. Previous scientific publications or experience from research and development projects are also
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tasks require a solid mathematical background with proven advanced experimental capabilities and excellent programming skills (e.g. C++, ROS, Matlab, etc.). You should have a strong vision to evaluate
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solid experience in machine learning (including deep learning), ideally in the context of computer vision and, more broadly, a proven track record in scientific programming (GitHub Repository or
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learning, programming, and analyzing visual data. Furthermore, you have the ability to work long-term and move projects forward even when challenges arise. You enjoy working towards results and