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, unit reliability analysis, and shared variance component analysis (SVCA) Create comprehensive data visualisations and perform statistical analyses to assess stability and plasticity of multisensory
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visual and auditory cortices using techniques such as cross-modal decoding, unit reliability analysis, and shared variance component analysis (SVCA) Create comprehensive data visualisations and perform
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About Us We are seeking experts in medical image deep learning to join our team and help develop novel computationally efficient segmentation algorithms. We welcome application from individual with experience in: Deep learning Medical imaging computing (preferably neuroimaging) Computationally...
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following skills and experience: Essential criteria PhD in statistical/psychiatric/behavioural genetics or a related academic area with a strong data analysis component Excellent coding skills with a focus on
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meetings between the research team and other stakeholders. There will also be elements of data curation, management, and analysis, supported by other members of the team. The successful candidate will hold a
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support the successful execution of this complex, multimodal study by contributing technical expertise in data acquisition, analysis, and pipeline development, ensuring methodological rigor and timely
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contributing technical expertise in data acquisition, analysis, and pipeline development, ensuring methodological rigor and timely delivery of research outputs. The ideal candidate will have experience with EEG
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retrospective analysis of the data. This will involve working with existing clinical data, extracting key variables, and compiling into an existing database template. The second component of the role is to make
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. Responsible for: Leading the optical and mechanical design of the microscope; integrating adaptive-optics modules, beam-shaping elements and bespoke detectors; developing synchronous control and lifetime
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use approaches which range from local micro-histories to large-scale quantitative analysis. We particularly value conversation between scholars of different periods and places, with different approaches