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Time series are an ever growing form of data, generated by numerous types of sensors and automated processes. However, machine learning and deep learning methods for analysing time series are much
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cooperating with each other, but in many cases competing for individual gains. This structure may not always work for the benefit of science. The purpose of this project is to use game theory and computational
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". A number of emerging approaches, such as zero resource and unsupervised NMT, have investigated alternative methods in developing NMT models where sufficient parallel corpora are not available (eg [1,2
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Statistical Methods, Automated Planning and/or Reinforcement Learning.
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Scholarship in CSIRO Industry PhD Program - Project 1: Resilient & Practical Quantum-Safe Threshold Cryptography Job No.: 678541 Location: Clayton campus Employment type: Full-time Duration: 4-year
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Scholarship in CSIRO Industry PhD Program - Project 2: Techniques and Frameworks for Enabling Post-Quantum Cryptography (PQC) Migration Job No.: 678538 Location: Clayton campus Employment Type: Full
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Research Training Program (RTP) Fees-Offset Research Training Program (RTP) Scholarships, funded by the Australian Government, support both domestic and international students undertaking Research
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privacy constraints, robust solutions are essential. This PhD project will develop methods for building reliable medical imaging models that generalize across distribution shifts without retraining
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I specialise in the numerical modelling of high-energy particle collisions , such as those occurring at the Large Hadron Collider. Accordingly, most projects I offer straddle the intersection
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models (e.g. tumour progression, tumour-drug sensitivity, survivability) by integrating multiple and heterogeneous data with associative data mining and ensemble learning methods.