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- $83,468 - $113,262 p.a. plus 17% super Contribute to innovative research in algebraic graph theory. Work with world-class mathematicians. Investing in you - benefits package including salary packaging
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University of New South Wales Canberra | Canberra, Australian Capital Territory | Australia | about 20 hours ago
the properties of integers through advanced algebraic and analytic techniques, with active research in additive combinatorics, exponential sums, and the distribution of primes. Who You Are (skills and experience
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or potential in areas such as: Mathematical quantum physics, including quantum information theory, C*-algebras, von Neumann algebras, and the rigorous mathematics of quantum field theory Strong or emerging
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areas such as: Mathematical quantum physics, including quantum information theory, C*-algebras, von Neumann algebras, and the rigorous mathematics of quantum field theory Strong or emerging research track
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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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with Lie Theory and Representation Theory. Working knowledge of packages of symbolic algebra, e.g. Maple or Mathematica. Evidence of experience in research and evaluation and the ability to work
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, structured light, photogrammetry). In-depth understanding of linear algebra and fundamentals of deep learning. Experience with deep learning frameworks (e.g., TensorFlow, PyTorch) and familiarity with latent
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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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applicant’s work will complement the established research and education strengths of the School which include algebra, analysis, geometry, topology, number theory, continuum modelling, mathematical biology
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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