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themes are not covered, including conventional medical imaging). Examples include Bayesian optimization for molecular or materials design; machine learning for single cell data; physics-based ML
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, including conventional medical imaging). Examples include Bayesian optimization for molecular or materials design; machine learning for single cell data; physics-based ML for turbine design and
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, including conventional medical imaging). Examples include Bayesian optimization for molecular or materials design; machine learning for single cell data; physics-based ML for turbine design and
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cortical neurons, functional loss-of-function approaches, single-nucleus RNA sequencing (snRNA-seq), xenotransplantation, and advanced in vivo imaging (e.g., 2-photon calcium imaging), the aim is to uncover
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across scales ranging from single bacteria, single host cells, 3D in vitro models to infected hosts. We have developed new imaging technologies to visualise the interface between the host and the pathogen
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for mechanistic analysis of meiotic crossover interference and high resolution imaging of single molecule dynamics of chromosomes Basic Qualifications expertise in high resolution imaging, knowledge of mitotic
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! Key responsibilities will include: Research: Support large-scale cognitive neuroscience research on brain stimulation, imaging, neurofeedback and neuropharmacology; develop a coherent research program
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methods will include training with data from Africa not normally available for routine forecasting, and we will explore the value of local optimisation or fine-tuning of foundation codes. Handling spatio
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in 2026 to outstanding researchers and practitioners from around the world to conduct paradigm-shifting creative practice and research based at any of Western Australia’s five universities
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methods Experience analysing RNAseq and/or high throughput imaging data Experience handling human post-mortem tissue Experience writing/using computer code Experience supervising postgraduate students and