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. The successful candidate will play a key part in ensuring the smooth running of the farm while supporting the delivery of high-quality practical learning experiences and research outcomes. Key responsibilities
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Australian National University | Canberra, Australian Capital Territory | Australia | about 10 hours ago
the proper operation of complex instruments, and assists in maintaining the Life Science facility. Reporting to the Senior EM Specialist and CAM Director, the role also supports teaching and outreach
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external partners. The incumbent will work as part of a team, contribute significantly to the efficient functioning of the DVCRIE Portfolio administrative support teams and observe a high standard of
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people and those from diverse cultural backgrounds. Proven ability and willingness to participate and support others as part of a dynamic, high-functioning team. Demonstrated planning, analytical, and
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geotechnical engineering. Expertise in constitutive and numerical modelling as well as coding. Experience with Linux-based high performance computing facilities desirable. A demonstrable track record in
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. You will also receive either: an Australian Government Research Training Program (RTP) fees offset a QUT research degree (HDR) tuition fee scholarship. As the scholarship recipient, you will have the
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qualifications in education, social sciences, evaluation, analytics, or a related field, or an equivalent combination of relevant experience and education. Demonstrated experience in program evaluation, data
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and policy advice. With proven leadership, you can set priorities, allocate resources, and drive a high-performing team. Your ability to problem-solve, engage stakeholders, and build consensus at senior
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matters including recruitment, performance management, policy interpretation, and case management. Act as a trusted advisor to staff and supervisors, ensuring consistent application of HR policies and
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to individualise tumour type, associated biomarkers and genomic characteristics to high precision. The resulting multipurpose machine learning workflows will lead to rapid precision diagnoses and effective