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This PhD scholarship is funded by an Australian Research Council Industry Fellowship grant. It is a 3.5-year research training program. The ARC Industry Fellowship program aims to develop a strong
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, you will: Support survey instrument design, testing and implementation Undertake data collection, cleaning, coding and analysis, including comparative analysis Assist with communicating results to a
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and protocols, statistical analysis plans. Prepare applications for data access and ethical approvals for datasets. Conduct research on risk of Alzheimer’s disease in women consistent with the project
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) environments for large-scale data analysis, including workload managers such as SLURM. For full details about this role, and other criteria, please review the Position Description . Not sure if you meet all
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development, implementation, and management of clinical trials and intervention programs. Assist in preparing trial operations materials and ethical approval. Manage participant data, including entry, analysis
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collaborate with senior researchers to design and implement impactful studies, analyse data, publish in leading journals, and support student supervision. You’ll also have opportunities to engage with industry
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, you’ll engage in a diverse mix of activities—from hands-on laboratory work, experimental design, and data analysis through to research publications, presentations, and student supervision. You will play a
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to demonstrate: A Completion of a PhD in a health-related discipline. Experience in qualitative and/or quantitative research methodology. The ability to plan and execute data collection and analysis. Experience
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Australian National University | Canberra, Australian Capital Territory | Australia | about 16 hours ago
record of publications and experience in laboratory experimentation and multiparameter data analysis. Experience in nuclear moment measurements is desirable. The candidate will be capable of developing
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, nucleic acids or other biomolecules is essential. Proficiency in scripting for simulation and data analysis, along with experience using high-performance computing environments, is required, and experience