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population genetics, bioinformatics, computational biology, statistics or probabilistic machine learning and computer science. Experience of working with large genotyping or sequencing data sets A proven
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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
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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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us to build/learn generative, probabilistic forward models of users and their physical and computational environments. This will involve modelling sensors, developing dynamic models for control and
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networks and/or probabilistic graphical models; and causal inference. An outstanding publication record in top tier machine learning and/or computer vision conferences or journals, commensurate with
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learning and one or more of the following: transformer networks, implicit neural functions, graph neural networks and/or probabilistic graphical models; and causal inference. • An outstanding publication
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AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | 10 days ago
deep learning theory and practice. Applicants with expertise in probabilistic modelling, approximate inference, deep learning, or Bayesian optimisation are encouraged to apply. Interpretable Machine
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work on both probabilistic modeling, software development, and cancer biology analysis for this position. PhD in computer science, computational biology, or related quantitative field. Strong oral and
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and statistical modeling for reliable analysis on spatial multiomic data. The candidate will work on both probabilistic modeling, software development, and cancer biology analysis for this position
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suggestions may include merging classes with low attendance, canceling classes with consistently low participation forecasts, proposing alternative time slots for specific classes, or reallocating classes