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Help shape the future of cancer care through better data. This PhD scholarship offers the opportunity to work with a leading research team using clinical trials and real-world data to build machine
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diseases will create an excellent environment for the training of PhD and MRES students. The Macquarie Medical School has active research programs in biomedical, translational and health services domains
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Multi-modal Machine Learning—including areas like Neuro-symbolic AI, Knowledge Graphs, Contextual AI, Conversational AI, and Trustworthy & Safe AI. This role also offers the opportunity to explore human
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-atomic potentials using a combination of classical and machine-learning (ML) approaches (and a new hybrid method recently developed in our group). Some of the types of simulations that will be performed
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the toxicity of degradation by-products. To be successful in this role, you will hold (or be near completion of) a PhD in chemistry, materials science, chemical engineering, or a related field. You will have
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science, machine learning, advanced computational design, and wearable technologies. To be successful you will need: Completion of a PhD in electrical, software, optical, biomedical engineering or physics
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experience contribute to ongoing translational research program related to the application of statistical and machine learning methods in reproductive and perinatal medicine using both clinical quality
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simulations using DFT (particularly of surface processes); kinetic Monte Carlo simulations; molecular dynamics simulations; classical and machine-learned force fields. Highly developed skills in scientific
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to generate data which can be coupled with robust and physics-informed machine learning and reduced-order modelling methods for model predictive control and reinforcement learning. PhD (or soon to be completed
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interactions. Machine learning: reinforcement learning, or multi-agent systems. Signal processing: spectrum sensing, localization, or radio environment modelling. Multi-agent systems: distributed intelligence