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AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | about 6 hours ago
high-impact practice Engage with regional communities in the development of community-led flood intelligence networks Position overview This fixed-term position will be based at the School of Art and
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board, to ensure the integrated model aligns with the project’s policy impact goals. Engagement and networking activities: Actively contribute and engage with the BSEER community, participating in in
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to the advancement of AI applications in biological sciences. This role presents a unique opportunity to work with pangenomic datasets while exploring the application of Large Language Models (LLMs) and machine
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Centre (AusSRC) is Australia’s portion of this international network, tasked with establishing and building capability to support the Australian and international SKA science communities, thereby ushering
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of the immense amount of data that will be flowing from the telescopes, the SKAO is working with science communities across the world through SKA Regional Centres (SRCs), which are nationally lead hubs that form
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systematic perturbation approaches. Systems Biology: Integrate multi-omic datasets to map the molecular networks influenced by mito-MPs. Machine Learning: Apply cutting-edge protein language models and AI
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on Treaty 6 territory, and respects the histories, languages and cultures of First Nations, Metis, Inuit and all FirstPeoples of Canada, whose presence continues to enrich our vibrant community
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project ‘The Cerebra Network’, funded by Cerebra. The Research Fellow will be split 50/50 between the two projects for the first three years (overall 1.0 fte), and then work solely on the Cerebra Network
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of seed gene networks”. This project aims to use reverse genetics, cross-species complementation and single cell next-generation sequencing approaches to investigate how the gene networks that regulate
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annotation of these metabolomes using multistage fragmentation (MSⁿ) data, incorporating novel computational methods and strategies (e.g. spectral matching, network-based approaches, machine learning) where