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analytical imaging methods, then working with collaborators to apply these methods to biomedical research, diagnostic imaging and beyond. Research projects vary from purely theoretical, to computational
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the development of numerical methods for astorphysical fluid dynamics and radiation transport. Projects may employ a range of approaches from analytic modelling and numerical calculations on desktop
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. The successful candidate will: Demonstrate strong analytical and research capability Demonstrate capability in design or creative-practice research Show interest in interdisciplinary and field-based research in
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research publications Possess excellent written and verbal English skills Demonstrate strong laboratory and analytical capabilities Have experience in concrete technology, cement chemistry, materials science
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analysis, case studies) Strong analytical and writing skills Desirable Skills Familiarity with energy, water, food or waste policy domains Experience with Multicriteria Mapping Interest in interdisciplinary
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linked-data cohorts, the National Centre for Healthy Ageing Data Platform and the 45 and Up Study, to develop analytical tools that can identify older adults at elevated risk of PRAC entry. A central focus
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practices in professional physics and students' engagement in these practices The role of agency in students learning physics practice A mixed-method, longitudinal study on factors related to retention in
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market, Role of EVs in the grid, Power System Stability Analysis Using Machine Learning Techniques and more. Eligibility Requirements: Applicants must be Australian citizens or Permanent Residents
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" "Machine-learning-based imaging processing" webpage For further details or alternative opportunities, please contact: haoran.ren@monash.edu.
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they bond in materials, but also develop transferable skills in scientific computing, data analysis and visualisation. "Machine learning for atomic-scale structure determination in thick nanostructures" (with