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-performance computing and geochemical modelling to decipher atmospheric CO2 removal mechanisms over geological timescales. The research involves integrating surface process simulations with tectonic frameworks
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physics. You will undertake high-impact research using data from the Large Hadron Collider (LHC) Run 3, with a focus on better understanding the Standard Model and identifying potential Beyond the Standard
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people who discover them The Opportunity Join an ARC-funded research project developing numerical methods to simulate the flow of dense viscous liquids through a deformable granular mush. The project aims
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focus on foundation models, medical image analysis, and multimodal healthcare data integration. In this role, you will: Develop novel federated AI methodologies, foundation model adaptation techniques
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excellence by providing a highly collaborative environment that benefits the research of all its scientists, whether at the graduate, post-doctoral or group leader level. A key initiative of the associate
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mechanisms underlying spinal cord injury and recovery. Operating within a highly collaborative and well-equipped environment, you will utilise advanced mouse models to solve complex biological questions
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highly collaborative environment that benefits the research of all its scientists, whether at the graduate, post-doctoral or group leader level. A key initiative of the associate membership is an EMBL
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performance. What You’ll Do Advance Rheological Discovery: Formulate and characterise model suspensions across Newtonian, shear-thinning, and shear-thickening regimes using state-of-the-art rotational and high
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staff recruited to the project and establish effective working relationships with the Chief Investigators, Joint Coordination Committee and other project members and work with the AI Modeller and ensure
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, including mixed effects, survival, growth curve and prediction models, to research in neuropsychology, epidemiology, neurodegenerative disease and cognitive disorders. We are seeking someone with a doctoral