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the WATOC Dirac Medal. As the successful candidate, you will contribute to the design and implementation of AI models that integrate quantum mechanical theory with deep learning, enabling rapid and
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in sequential decision-making approaches such as Markov Decision Processes, reinforcement learning, deep learning, or adaptive management. You have a strong track record of research publications and
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architecture design, simulations, and publicly available genomic datasets to develop new inference methods. The Postdoctoral Associate will conduct research related to creating or testing deep learning models
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optimization of multi-modal LLMs. Investigate and implement methodologies to ensure AI authenticity, accountability, and the integrity of digital content. Develop and refine machine learning and deep learning
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: Bayesian Machine Learning – Led by Dr Thang Bui, this project focuses on sequential decision-making and bridging deep learning theory and practice. Applicants with expertise in probabilistic modelling
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control using deep learning. Implement and test new algorithms in actual robot platforms. Job Requirements: PhD in Electrical and Electronic Engineering or related field. Hands on research experiences in
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of directly related experience. Knowledge / Skills / Abilities Knowledge Deep understanding of evidence-based teaching and learning practices across multiple modalities. Knowledge of faculty pedagogical
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prediction models in Neurology using EEG data via Deep Learning (DL) techniques. In this prospective and longitudinal study, the outcome of interest is cognition over time. This position will be under
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international specialists. Within Cumulus, you will lead the development of “downscaling” methods for sub-seasonal (2-4 week) forecasts. Our priority will be to implement deep-learning based methods, to turn
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. Are you a Computer Scientist looking to apply your expertise to real-world weather forecasting challenges in Africa? Machine-learning has the potential to revolutionise weather prediction for and in Africa