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, or similar. Familiarity with linear algebra libraries and high-performance computing is a merit, but not a requirement. About the position The position provides you with the opportunity to pursue PhD studies
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, CUDA, etc. Experience with numerical methods such as FDTD, FEM, BEM, etc. Basic knowledge of numerical linear algebra concepts, such as matrix factorization and decomposition algorithms. Familiarity with
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mathematical concepts such as optimization, linear algebra, probability, and statistics, relevant to AI and quantitative modelling. Technical proficiency in programming66: Demonstrated programming skills with
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Master’s degree (or equivalent) in mathematics, computer science, physics, or related field. Sound knowledge in (scientific) machine learning, and knowledge in numerical analysis and numerical linear algebra
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, or equivalent) Strong academic track record, with exceptional grades in advanced mathematics, theoretical physics, or computer science courses. Strong understanding of linear algebra, calculus, differential
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shadows Strong mathematical education, in particular in relation to linear algebra Programming experience is a plus Ability to effectively communicate in written and spoken English Ability to work
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algorithms and deep learning models. Have proficiency in Python in a Linux environment and development experience using Tensorflow or PyTorch. Have strong linear algebra and computer vision knowledge. Have
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structures, etc to solve challenging problems is required (there will be a practical coding assessment during recruitment) A solid mathematical foundation is required (multivariable calculus, linear algebra
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with Python or C. Solid understanding of linear algebra, calculus, and probability theory. Strong background in machine learning and deep learning is highly preferred. The ideal candidate will have