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the construction of PRS and enhance disease prediction. Students will gain experience in: Statistical genetics and GWAS methodology Machine learning approaches for high-dimensional data Algorithm development and
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include: Data analysis, statistical modelling, and algorithm development to support work with the Department of Defence. Develop code in R and Python. Provide statistical, mathematical, and optimisation
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through theory and simulation and/or experimental design and testing; developing new image reconstruction algorithms for providing more information with less radiation; and applying our techniques
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emissions”, which is funded by the Trailblazer for Renewables and Clean Energy (TRaCE) and industry partner, CounterCurrent Pty Ltd. The project builds upon the prototype ship route optimization algorithm
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AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | 2 months ago
interface to humans with varying expertise in real-world responsible AI scenarios. The successful candidate will design and develop new AI algorithms and systems, engage with a dynamic research group within
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, TensorFlow, or JAX) Experience with photonic design techniques and global optimisation algorithms (Genetic Algorithms, Particle Swarm, Gradient Descent) Experience implementing deep learning architectures
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of masculinity, especially in relation to younger male audiences. The successful applicant may explore such questions as: What drives engagement with manosphere communities? How do algorithmic systems and platform
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-autonomous systems, and their applications to complex ecological networks design and implement novel coordinate-independent numerical algorithms utilising automatic differentiation and pseudo-arclength
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Research Associate in Logical Foundations of Planning. In this role you will work closely with Dr Rubin on research projects, and contribute to the collegial culture of the Sydney Algorithms and Computing
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formative assessment and personalised feedback while ensuring fairness, accountability, and transparency. The research will explore a combination of algorithmic design, human–AI interaction, and empirical