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University of Adelaide. Applicants should have a background in health or medical sciences, with an understanding of variations in the healthcare system across Australia. The ideal candidate should have some
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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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scientific data from seabed, communications between underwater robots and vehicles. However, the performance of underwater acoustic communication is restricted by time and frequency variation, reverberation
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understanding of gene presence/absence, structural variations, and evolutionary dynamics. In this project we will aim to develop novel dynamic programming computational methods for pangenome assembly of diploid
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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
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) + Finite element methods for complex flows in porous media (generalized multiscale finite elements via autoencoders, adaptive in space and time, splitting methods, and variational flux recovery) + Adaptive r