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Field
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Qualifications PhD in Animal Science, Agricultural Economics, Sociology, Environmental Science, Global Development, or other fields with relevant experience. Demonstrated experience with collection and/or analysis
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. The objectives are to conduct cutting-edge research where local themes are connected to global issues of water and climate, with a focus on: Integrated Water Resources Management (IWRM) Development of water
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develop or implement new computational analysis pipelines. The researcher will be expected to work closely with wet-lab scientists to integrate the analysis of omics data and wet-lab experimental results
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development activities at the intersection of Agentic AI, AI Security, Trustworthy AI, Software Engineering, and Cybersecurity. The group is developing novel methods, tools, and platforms to support the safe
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to develop rapid, generally applicable workflows for the discovery and utilization of bioactive molecules derived from plants. We are looking for a talented and motivated postdoctoral fellow with a research
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knowledge of developing AI-based information systems, such as AI-enabled engagement e.g., agentic AI and AI-enabled insight generation e.g., machine learning analytics in both individual and organizational
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their absolute ground states at temperatures around 1 microKelvin, and explored their interactions and collisions. We are now developing the use of these and other ultracold molecules for quantum science. Further
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available at http://antarctic.org.au/ Develop and interpret past climate records from Antarctic ice samples, including those collected during the 2023/24 Denman Terrestrial Campaign. Undertake high-quality
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. Mentor and train undergraduate students in the lab. 5% 4. Prepare proposals for postdoctoral fellowships. 5 % 5. Present research findings at local and international
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IOCB Prague (Institute of Organic Chemistry and Biochemistry of the Czech Academy of Sciences) | Czech | 3 months ago
cutting-edge experimental (e.g., LC-MS, metabolomics, RNA-seq) and computational (e.g., bioinformatics, molecular networking, machine learning) approaches to develop rapid, generally applicable workflows