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research team to unravel the neural pathways of speech in Parkinson’s disease, combining advanced MRI, speech analysis and neuromodulation to drive impactful scientific discoveries. We invite applications
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qualitative methods and analysis approaches. You have experience in collecting and analysing qualitative data, ideally in relation to the themes of this project. You have experience with conducting fieldwork
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, cognitive science or a related field, and have solid knowledge of human movement analysis (e.g. motion tracking) and neuroscience methods (e.g. EEG). You have previous experience working with human subjects
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infrastructure into the European innovation ecosystem. ScaleUA involves innovation systems analysis, infrastructure mapping, governance design and investment prioritisation across three strategic sectors: energy
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or are willing to acquire the relevant skills during your PhD project. You have an affinity with Digital Humanities, especially with network analysis and visualisation tools (e.g. Nodegoat, Gephi). You are able
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(confocal and super-resolution microscopy), single-molecule FISH, viral gene transfer, single-cell/single-nucleus transcriptomics, whole genome sequencing, mouse and Drosophila behavioural analysis
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. ScaleUA involves innovation systems analysis, infrastructure mapping, governance design and investment prioritisation across three strategic sectors: energy, digital technologies and health. The project is
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(Master’s degree) in neuroscience, biomedical engineering, medical biology, human movement science, cognitive science or a related field, and have solid knowledge of human movement analysis (e.g. motion
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XAI and metadata creation, including both image and text analysis. You will organise benchmarks that assess AI technologies, particularly in the domain of newspapers, both current and historic. Further
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have an affinity with Digital Humanities, especially with network analysis and visualisation tools (e.g. Nodegoat, Gephi). You are able to conduct independent academic research and present your findings