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on brain and behavioral development in youth, along with pediatric anxiety and PTSD, using fMRI, anatomical MRI, genotyping, blood biomarkers, and psychophysiology. This position centers on multimodal data
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discipline and demonstrated expertise in MRI processing and analysis, supported by first-author publications. You will have strong analytical, programming and scientific writing skills, with experience using
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on application expertise and interest; Generation and analysis of mass spectrometry based exposomics data; Analysis of multiomics data; Analysis of MRI-derived imaging data; Provides guidance and support to PhD
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on application expertise and interest; Generation and analysis of mass spectrometry based exposomics data; Analysis of multiomics data; Analysis of MRI-derived imaging data; Writing narrative summaries
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work and strong scientific writing. Preferred Qualifications Familiarity with spectral analysis and signal processing of heart rate / ECG data (e.g., frequency-domain HRV). Experience with MRI data
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would work as a clinical research fellow on this project and be responsible for participant screening and recruitment, clinical assessments, and performing study visits with MRI and PET scanning
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in sympathetic/parasympathetic balance; link sleep metrics to CAAN’s primary outcomes: LC structure and function (MRI), CSF and plasma biomarkers, proteomic markers of mitochondrial stress, daytime
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well as AI-driven approaches for treatment outcome prediction and clinical decision-making. Projects involve multimodality imaging data, including CT, MRI, PET, and Ultrasound, as well as clinical radiation
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frameworks (e.g., persistent homology, Ricci flow) to characterise tissue architecture and spatial organisation in transcriptomics data. Experience analysing radiological imaging data, particularly MRI, and
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communication skills. Experience of acquisition and analysis of relevant clinical and neuroimaging data (eg PET, MRI, EEG, MEG). Desirable criteria Experience of supervision of students/ researchers in conducting