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Field
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propagation solely through spatial structures, we develop THz time-varying photonic systems based on subwavelength waveguides, where ultrafast excitations modify the optical properties of a material on the
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for extreme weather conditions (heat and rain), urban greening for biodiversity, or electrification to decarbonise housing and industry. In addition to conventional qualitative methods such as document analysis
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fields; • experience with large datasets, spatial and environmental analysis, and field work will be viewed favourably; • proficiency in R or similar scripting languages for data cleaning, analysis and
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We hereby invite applications for one or more PhD position focusing on the development and application of hyperspectral imaging technologies for bulk forensic evidence analysis. The project aims
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characterising spread of material for future star formation. Simulation and observational analysis of star formation regions as mission prep for planned NASA SMEX mission Eos and potential Monash cubesat project
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to increasing traffic loads and environmental effects, efficient methods for monitoring their condition become essential. Traditional inspection approaches can be costly, time-consuming, and limited in spatial
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on genetically and optically tractable arthropod species that satisfy a number of appealing biological and technical requirements. We combine advanced microscopy and image analysis pipelines with genetic and
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. Traditional inspection approaches can be costly, time-consuming, and limited in spatial and temporal coverage. This PhD project addresses these challenges by developing innovative methods to assess railway
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and ML libraries (e.g., NumPy, SciPy, PyTorch/TensorFlow, scikit-learn). Experience with spatial data analysis, interpolation techniques, or geostatistical concepts variography, kriging, conditional
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with regard to both spatial and temporal evolution. • Investigate mechanisms controlling radionuclide retention and transport in cementitious and geological materials. • Assess the influence