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systems. Experience with batteries, power systems, EV/aviation systems, stochastic/robust optimisation, or IGDT. How to apply: Send 1) CV, 2) transcripts, 3) a 1-page statement addressing fit and your most
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the academic staff at SIT. We are looking for PhD students to work on projects on stochastic optimisation algorithms for hyper-parameter tuning in Machine learning. The successful candidate will explore
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: "Revealing the foundations of physics via gravitational waves from the early Universe" "Understanding the origin of visible and dark matter through the stochastic gravitational wave background" "Uncovering
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-refinement for finite element and scientific deep learning methods (gradient-free adaptation, generalized stochastic gradient descent methods) Salary for PhD students: is AUD32K per annum, tax free