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Field
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, and mathematical data science, with an active programme at the interface of dynamical systems, machine learning, and quantum information. The position sits in the GOAL group (GeOmetry, dynAmics, and
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to investigate light absorption and emission, charge-carrier dynamics and transport, defect states, local energetic landscapes, and spatial heterogeneity. • Develop, optimize, and operate advanced optical
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, with expertise in dynamic/data-driven modeling, optimization, Aspen, COMSOL, or CFD b. Techno-economic analysis (TEA) & life-cycle assessment (LCA) for chemical, energy, or biomanufacturing processes
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-funded research program focused on decoding cardiomyocyte subtype dynamics and molecular mechanisms underlying heart failure progression. Led by Didi Ren, Ph.D., Principal Investigator, the lab integrates
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computational chemistry, reaction network analysis, and machine learning for organometallic catalytic reactions. 2. Design of membrane-permeable macrocyclic peptide drugs via machine learning structure
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designing and conducting experiments, developing and integrating photoacoustic and ultrasound systems, validating technologies in animal models, and performing quantitative data analysis and computational
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the Australian Research Council and UNSW Sydney. The project seeks to advance the analysis of dynamical systems through the development of novel techniques in functional analysis, operator theory, ergodic theory
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designing and conducting experiments, developing and integrating photoacoustic and ultrasound systems, validating technologies in animal models, and performing quantitative data analysis and computational
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proteins, nucleic acids and their complexes through an integrative structural biology approach. The laboratory combines experimental and computational methods to understand biomolecular structure, dynamics
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will focus on efficient probabilistic analysis of high-dimensional and dynamic systems, including advanced sampling, surrogate modelling, and AI or machine-learning methods where appropriate. Key