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. Demonstrated experience in the analysis and interpretation of omics datasets, with strong expertise in artificial intelligence and machine learning methodologies. Proven experience in the analysis of single-cell
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(e.g., Docker, Kubernetes, cloud/edge environments). Demonstrated expertise in AI, distributed computing, machine learning, or systems software design. Strong background in software engineering
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, machine learning, and causal inference frameworks that link genetic variants to cellular mechanisms and therapeutic opportunities. Our research spans immune biology, cardiac disease, neurodegeneration, and
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geometry, and/or data science. Specific topics of focus include, but are not limited to, linear response, random and nonautonomous dynamical systems, spectral analysis, machine learning, data-driven dynamics
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relevant to integration of machine learning and mechanistic models, and development of engines for efficient processing and visualisation of large-scale datasets and system geographic information and
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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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fostering “leadership, learning, and empathy between cultures… It is a modest program with an immodest aim – the achievement in international affairs of a regime more civilised, rational and humane than
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Institute for Machine Learning – the largest computer vision and machine learning research group in Australia – and contribute to world-leading research projects at the Centre for Augmented Reasoning
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. We offer a range of undergraduate and postgraduate courses and have active research programs specifically oriented around Cyber Security and AI/Machine Learning with a growing, multidisciplinary
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Academic Level B: Completion of a PhD in the field of Computer Science/Artificial Intelligence. Software engineering expertise, including design and implementation of AI-based models (machine learning, deep