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AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | 13 days ago
click here . ANU is a large, diverse employer with staff working across numerous professions (see the full list of available roles here . We are a recipient of the bronze award through the Science in
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Sciences, Urban Studies, Engineering, and Computer Science to advance research on climate change and global grand challenges. The School of Project Management in the Faculty of Engineering at the University
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AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | 27 days ago
) Country Australia Application Deadline 24 Nov 2025 - 00:00 (UTC) Type of Contract Other Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is
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to a program of research that informs immunisation policy and practice through evidence-based insights. You will work closely with a collaborative team of experts and contribute to expanding the group’s
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Biostatistics/Methods Stream and Microbiome/Multi-omics/Data Science Stream knowledge as detailed in the attached position description. A job share arrangement may be considered. As an Associate Research Fellow
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methods. Assist with the supervision of research students in the research area where required. Liaise with national and international collaborators to ensure satisfactory project progression. Program
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evaluate methods via experiments, benchmarking, simulation and/or real‑world data. The successful candidate will have: A PhD in Statistics, Data Science, Computer Science, Mathematics, or a related field
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Job Reference: 1122969 About the Role: You’ll be joining an exciting ARC-funded research project developing cutting-edge computational methods to predict and understand the organic crystal
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School of Electrical Engineering and Computer Science Full-time (100%), fixed-term position for up to 3 years Base salary will be in the range $114,824.05 - $136,048.72 + 17% Superannuation
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Performance . About You The successful candidate will play a key role in the development and validation of computational tools that integrate spatial transcriptomics, algorithmic methods, and machine learning