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imaging; classical imaging; multiphoton imaging; the development and application of numerical methods of deep learning or multivariate analysis. Interdisciplinary experience with projects that overlap
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, stability/perturbation theory/rigorous numerics. Possible applications of the new theory include the analysis of spatiotemporal data arising from weather and climate observations/models and from models
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at the University of Sydney is currently seeking a Postdoctoral Research Associate (Physics) to work within the Dynamics and Neural Systems Group, led by A/Prof Ben Fulcher, on developing novel methods to analyze non
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Job no:520746 Work type:Full Time Location:Crawley Categories:Engineering and Mathematical Sciences, Social Sciences Lead numerical modelling of carbonate sand for offshore foundations, support
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fabrication, with the ability to prototype and test light delivery and optical feedback systems. This role also involves conducting numerical modelling of light propagation in biological tissues, contributing
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and Ar-Ar geochronology, fission-track and (U-Th-Sm)/He thermochronology, vitrinite reflectance, and thermal history models. New relational data models data for incorporating methods such as include
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quality standards. Apply specialist technical expertise — develop, set up, and monitor experiments, research protocols, and analytical methods under broad direction. Maintain accurate documentation — record
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imposed timelines/milestones. PhD (or near completion) in Engineering or Applied Science with strong expertise in CFD. Proficiency with open-source engineering software and numerical methods such as FEM
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in appropriate qualitative and quantitative research methods, software and tools in a relevant research context. Proven scholarly writing skills (Level D) and experience in preparing publications for a
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advanced computational and genomic approaches. The successful candidate will work as part of a funded research project that integrates metagenomics, k-mer–based methods, and artificial intelligence