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(7T fMRI, MR Spectroscopy), electrophysiology (EEG), interventional (TMS, tDCS) and neurocomputational (machine learning, reinforcement learning) approaches to understand the network dynamics
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while also offering scalability to dynamic and complex environments. The PDRA will also lead in-field testing and deployments. Therefore, we require someone with excellent implementation skills and
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this, the Fellow will implement a universal design methodology for such fluids of complex rheology, using a Machine Learning (ML) algorithm to be incorporated in a Computational Fluid Dynamics framework. Training
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analysis techniques, including space syntax, isovist measures, and visual complexity assessments. The successful candidate will work closely with researchers at Cambridge and ETH Zurich to quantify spatial
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, green business, decision support. Understanding of the net zero and/or circular economy. Research Excellence Proven strong track record of high-quality publications. Ability to work independently and
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The post-holder will join a team of investigators working on the NERC-funded Pushing the Frontiers grant ‘Influence of complex source and environmental source conditions on eruptive plume height
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: Otaniemi Campus, Espoo, Finland Join a cutting-edge research environment where architecture, landscape architecture, and artificial intelligence meet to address complex environmental challenges. About the
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research project, Understanding health and well-being among farm women: A life-course approach, which is jointly led by the CRPR and the Farming Community Network (FCN). Through a combination of quantitative
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post is designed to offer a unique opportunity to work at the intersection of academic research and agricultural policy, developing and disseminating new knowledge for networks of UK farmers
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flexible working, Enhanced Parental Leave, funds for Parents and Carers, and the potential to join community staff networks. About the role You will join a team of climate scientists and artificial