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applied mathematical modelling machine learning multi-fidelity modelling numerical methods. Demonstrated programming ability (MATLAB/Python/C++) and enthusiasm to learn PyTorch. Previous experience in one
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in finite element modelling and machine learning (desirable). How to apply Apply for this scholarship at the same time you apply for admission to QUT's Doctor of Philosophy . *The first step is to
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materials systems at the molecular level with machine learning. The PhD Student will work with tumour sections to develop multiple instance learning and weak supervision / spatial transcriptomics models
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study flow dynamics relevant to reactor design using optical diagnosing methods, followed by image processing, which may include machine learning-based techniques. This suits Mechanical Engineering
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microfluidic fabrication and experiments 3D printing machine learning. Demonstrated programming skills (Matlab, C++, or Python). Desired Demonstrated ability to work independently and to formulate and tackle
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models that can forecast the likely outcomes of current practices. The project aims to develop cutting-edge machine learning and statistical risk prediction techniques to predict each short-term, long-term
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science technologies, and this is a perfect training opportunity for those who is interested in machine learning, data mining, artificial intelligence, and bioinformatics. High-performance computing may