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(CRISPR screens, Chromatin IP, ATAC-seq) and cellular biology (cell death mechanisms, immunology), and experience with animal models and organoid cultures. Position 3 will focus on Bioinformatics
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essential, mathematical theory frequently suggests its value is low. This misalignment creates a gap between modelling and practice. The research will focus on developing new theory to explain why
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AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | about 2 months 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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metapopulation and/or individual based models Knowledge of Bayesian methods, including Approximate Bayesian Computation Experience with big data analysis and HPC environments Knowledge of additional programming
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Melbourne CBD campus About the Role We are seeking a Postdoctoral Research Fellow to join RMIT's Materials Modelling and Simulation group to apply classical Molecular Dynamics and Machine Learning approaches
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at the RMIT Melbourne CBD campus About the Role We are seeking a Postdoctoral Research Fellow to join RMIT’s Materials Modelling and Simulation group to apply classical Molecular Dynamics and Machine Learning
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engineering. About the opportunity Play a key role in advancing the AuScope Geochemistry platform ‘EarthBank’ at UWA. Contributing to new and existing analytical datasets and data models, improving
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will support the delivery of funded research project from CSIRO AR-PST. You will also contribute to other research activities related to inverter system and load modelling, small-signal and voltage
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independently and design/interpret experiments using in vivo animal models and ex vivo methods, adhering to PPE requirements (including PAPR use with restricted carcinogens). Demonstrated critical thinking
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health lens to addressing hearing loss in adults. This program aims to reshape how hearing care is viewed and delivered—shifting from a specialist-driven, clinic-based model to a more accessible