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/ [Work content and job description] 1. Research on the above area 2. Teaching undergraduate and graduate courses of the Department of Mathematics and basic courses on Linear Algebra and Calculus
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/ [Work content and job description] 1. Research on the above area 2. Teaching undergraduate and graduate courses of the Department of Mathematics and basic courses on Linear Algebra and Calculus
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follow specialized training programs (e.g. ARENA). Specific Requirements Knowledge: Linear algebra, probability and statistics. Graph theory and algorithms on graphs. Machine learning and deep learning
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candidates hold a Master’s degree in Informatics, Mathematics, or a related field, and possess strong expertise in linear algebra, GPU architectures, and programming in C++ and Python. This is a 100% TVL E13
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: Algorithms for optimisation, sampling, linear algebra and scientific computing; provable quantum speedups and rigorous analysis of their resource requirements. Quantum software, architectures and compilation
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. The ability to teach linear algebra is preferred but not required. Academic Environment and Faculty Support GU-Q offers a rich academic setting supported by strong institutional resources to enable excellence
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: strong foundations in linear algebra, probability theory, and calculus solid skills in programming interest in mathematical and statistical method development, good communication skills and sufficient
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programs in mathematics, science, education, and engineering. Teaching responsibilities may include calculus, linear algebra, numerical analysis, discrete probability, mathematical modeling, and related
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in supporting students across disciplines who require quantitative coursework. The ability to teach linear algebra is preferred but not required. Academic Environment and Faculty Support GU-Q offers a
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, calculus, and linear algebra) and advanced courses in mathematics, statistics, and actuarial science for students majoring in actuarial science, applied mathematics, mathematics education, and other fields