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collecting and analysing interview and interactional data. This will enable the co-design, testing, and implementing of a new training program to improve how assessments are communicated with clients and
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microorganisms, using data from field and laboratory experiments that include functional trait measurements, plant and microbial physiological data, and genomic data. The aim of the project is to link
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analytical characterisation (e.g., LC-MS). Patch-clamp electrophysiological measurements of peptide activity against a range of voltage-gated ion channels, especially voltage-gated potassium channels
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Australian National University | Canberra, Australian Capital Territory | Australia | about 2 months ago
and Host Area The School of Computing has a strong foundation in computing and information sciences at ANU. We are a transformative centre for research in artificial intelligence and machine learning
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bring demonstrated analytical skills, a track record of peer-reviewed publications and experience in data extraction for systematic reviews or meta-analyses. Strong proficiency with software tools such as
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unique data collection opportunities, including large-scale agricultural household surveys, measurement experiments (such as DNA fingerprinting for plant variety identification), and impact studies
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activities via five broad focus areas: Computing Foundations, Computational Science, Intelligent Systems, Data Science and Analytics, and the Software Innovation Institute. Be part of an innovative and forward
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building a digital platform that consolidates and presents this information. Centred on data extraction and expert review, the position involves assessing the accuracy and appropriateness of scientific
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leading medic-legal and engineering researchers on real-world crash data Join Australia’s only academic department embedded in a forensic medicine institute The Opportunity Are you a proactive early-career
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for (Selection Criteria): Essential: A doctoral qualification in a relevant engineering, computing, or physical sciences discipline. Demonstrated research expertise in data analytics, machine learning, artificial