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/operations research, or an equivalent qualification and must have no more than five years of post-qualification experience at the time of application; and (b) solid mathematical background. Applicants
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, including machine learning, computer vision, adaptive data modelling, and computational imaging. The objective is to develop state-of-the-art machine learning algorithms for solving ill-posed inverse problems
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, including machine learning, computer vision, adaptive data modelling, and computational imaging. The objective is to develop state-of-the-art machine learning algorithms for solving ill-posed inverse problems
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be close to completing a PhD in computer science, mathematics, or a related area with a topic close to type theory or constructive mathematics. Expertise can be evidenced through publications
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, quantitative field, e.g. atmospheric or climate science, meteorology, computer science, data-science, physics, mathematics, statistics, environmental science or related fields Evidence of a good understanding
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platform with global ambitions. The Position Funded through the Medical Research Future Fund (MRFF), this position will play a central role in developing computational tools and AI-based approaches
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on high performance computing systems in a way that is suitable for operational use. Implement and test different ML architectures, such as convolutional and encoders-decoder ANNs for predicting flooding in
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cilia and nuclear signaling in the brain. Position Summary: We seek a candidate with strong expertise in microscopy and computational image analysis to: Support and enhance ongoing imaging projects in
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obtaining, a PhD in computer science, engineering, mathematics, or a related physical sciences discipline, with research expertise in areas such as hardware-aware AI security, approximate computing, or secure
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Therapy, Computer Science, Engineering, Mathematics, Science, Physics, etc). Emerging track record publishing in high quality journals (e.g., Medical Physics, IEEE, etc.). Experience presenting at high