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materials systems at the molecular level with machine learning. The PhD Student will work with tumour sections to develop multiple instance learning and weak supervision / spatial transcriptomics models
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understand its fundamental causes has been limited to animal models and trials. There are over 27 animal models for neuropathic pain where pain has been induced by macroscopic & microscopic nerve lesions
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techniques, theoretical modelling, and precise synthetic control – have significantly improved the activity, selectivity, and stability of CO₂-to-alcohol conversion. Key catalyst systems include Cu-based
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submission within a couples therapy. Aims The project will aim to develop and test a model of how couples resolve imbalances along the dominance and submission dimension during couples therapy. Objectives
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PhD student(s) will join a vibrant team of postdocs, academics, and up to four PhD students working collaboratively across modelling, qualitative fieldwork, and optimisation techniques. PhD Research
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materials systems at the molecular level with machine learning. The PhD Student will undertake a study analysing mass spectral imaging data streams in real time using machine learning workflows. A pathway for
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the structure present in food systems dictates functional aspects such as digestion and release of nutrients. Working alongside other postdocs and students focused more on biological aspects of these processes
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, there is an urgent demand for accurate data on ion-beam collisions with atomic and molecular targets for the development and maintenance of fusion reactors, treatment planning in hadron therapy, and
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Martin Australia invite applications for a project under this program, advancing robotic perception systems through monitoring of their machine learning models. Run-Time Monitoring of Machine Learning
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, using toxic molecular reactants rather than renewable electricity. One obvious solution toward integrating renewable electricity into chemical manufacturing is to electrify industrial organic reactions