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and conducting laboratory work. Insight into applied mathematics, linear algebra, process-based modeling, and soil health indicators. Experience with Python, applied statistics, and gradient-based
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benefits are in accordance with the German public sector scale, TV-L E13. Your Qualification: Strong mathematical background (e.g., linear algebra, optimization, formal methods, convex geometry). Master's
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involve combining highly sophisticated tools for numerical analysis, scientific computing, algebraic topology and non-linear analysis. - activities: The activities may include: The development of new
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) understanding of the mathematical foundations and principles of Machine Learning, Linear Algebra (vectorial and matricial operations, optimization), with a particular focus on Neural Networks, 3) problem solving
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analysis, scientific computing, algebraic topology and non-linear analysis. The activities may include: The development of new polytopal numerical methods The conception of discrete complexes (de Rham and
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development of team members. Qualifications and experience essential PhD in Applied Mathematics in the fields of Numerical Linear Algebra, or equivalent. Prior experience on the subject is highly desired. Where
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The Institute of Mathematics of the Czech Academy of Sciences (IM CAS) is seeking a researcher for the Czech-Polish international project “Modern geometrical aspects of linear operators: matrix representations
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, statistics, calculus, and linear algebra); Have strong communication, presentation and writing skills; Enjoy working in a multidisciplinary research environment; Are highly motivated and creative; Have an
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). A deep foundation in advanced mathematics, including differential equations, linear algebra, tensor calculus, and group theory; and the ability to use these for formal, mathematical reasoning
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of numerical quantum many-body methods to study model Hamiltonians. Strong background in linear algebra. Preferred Qualifications: Experience with density matrix renormalization group and tensor network