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society, computational social science, and psychology. We invite applications for a full-time postdoctoral researcher to join the interdisciplinary SNSF-funded research project "Digital Originals in 3D
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stimulation (tES). Primary activities include preparing tES electrodes, supplies, and other study-related materials, data management (paper and digital), computer-based MRI analysis requiring programming skills
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processing in the mammalian cochlea in vivo , and how these influence central auditory neuronal pathways. The project will primarily involve using in vivo 2-photon imaging and AAV-gene delivery applied to a
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departments: Cardiovascular Imaging, Cancer Imaging, Early Life Imaging, Imaging Chemistry & Biology, Biomedical Computing, Surgical & Interventional Engineering, Imaging Physics & Engineering and Digital Twins
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Doctoral Associate Duke Department of Neurosurgery This Postdoctoral Associate position will play a critical role in making the use of new imaging tools more automatic and streamlined. Key responsibilities
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solutions informed by the latest ideas in medical imaging AI, computer vision and robotic guidance; and evaluate models in simulated and real clinical scenarios. Evaluation may involve quantitative studies
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departments: Cardiovascular Imaging, Cancer Imaging, Early Life Imaging, Imaging Chemistry & Biology, Biomedical Computing, Surgical & Interventional Engineering, Imaging Physics & Engineering and Digital Twins
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: Ph.D. in Electrical Engineering, Applied Mathematics, Biomedical Engineering, Mechanical Engineering or related fields. Preferred Experience: Experience in MRI and post-imaging processing Preferred Field
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characterization platforms, state-of-the-art microscopy resources, and computational tools for systems biology approaches. The position emphasizes rigorous mechanistic investigation using both in vivo (C. elegans
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standard software programs including Microsoft Office (Word, Excel, PowerPoint). Knowledge of computer programming/scripting (e.g., Matlab, Bash/Unix). Knowledge and experience using image/EEG analysis