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geometry, connecting algebraic combinatorics, algebraic geometry, and high-energy physics . We invite applications for postdoctoral positions to join this interdisciplinary program. Successful candidates
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foundations and principles of Machine Learning, Linear Algebra (vectorial and matricial operations, optimization), with a particular focus on Neural Networks (pytorch), 3) problem solving skills, 4) familiarity
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in high performance scientific computing, multi-linear algebra and tensor contractions for heterogeneous exascale architectures. The successful candidate will join the NumPEx PEPR to reinforce
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courses in the academic year with four (4) in the fall semester and four (4) in the spring semester (lower and upper level such as Calculus, Discrete Mathematics, Linear Algebra, and Differential Equations
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(8) undergraduate courses in the academic year with four (4) in the fall semester and four (4) in the spring semester (lower and upper level such as Calculus, Discrete Mathematics, Linear Algebra, and
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PhD in Physics Strong background in quantum mechanics and linear algebra Research experience in quantum information or quantum foundations Publication record in peer-reviewed journals Experience with
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are essential. Experience with a computer algebra system such as Mathematica is an advantage. We are also looking for good written and verbal communication skills. The Gravitation and Cosmology Group at Sheffield
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and coding using either Python or Mathematica are essential. Experience with a computer algebra system such as Mathematica is an advantage. We are also looking for good written and verbal communication
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significantly influenced its academic development. The successful candidate will: -Teach undergraduate and graduate mathematics and applied mathematics courses (such as calculus, linear algebra, differential
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development spanning areas such as optimization, Fourier analysis, numerical linear algebra, statistics, machine learning, and high-performance computing for one or more of the following: (1) reconstruction