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Field
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prioritise RD as a mechanism for ecosystem resilience. The project will use Agent-Based Policy Modelling (ABPM) to simulate how actors such as land managers, farmers, local authorities, and conservation
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of coronary artery disease and supporting clinical decision-making during catheterization procedures. The project brings together cardiovascular imaging, generative AI, and computational modeling to develop
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, modelling, prototyping and experimental validation. The best fit is A candidate interested in high-frequency measurement techniques, sensor hardware development and precision experimentation. PhD 2
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for probabilistic unsupervised learning for structured biological data. The successful candidate will: Develop probabilistic factor models and scalable inference algorithms for structured biological (multi-view) high
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requirements to train vision foundation models. When applying, you are required to clearly motivate why you are a good fit for this position and how your expertise and previous experience match the position
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in auditory neuroscience, neuroimaging, and AI/NeuroAI. In this role you will bridge human neuroimaging and computational modelling . You will collect and analyse neuroimaging data (7 Tesla fMRI
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approach that includes stakeholder engagement, behavioural science, design research, transition studies, and modelling, the project aims to develop empirically grounded interventions and governance
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leader is Associate Professor Soledad Gonzalo Cogno. About the project The successful candidate will contribute to the development of mathematical and computational models to enquire about the mechanisms
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. Extensive experience with mouse models is desirable, including preparation of pre-operative brain tumor cell suspensions, stereotactic orthotopic xenograft implantation of brain tumors in mice, and use
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supports numerical computational modeling of subsurface flow and well performance, mentors PhD students, and contributes to ongoing research projects. This is a temporary, part-time (wage-payroll) hourly