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international level. Candidates that fit into this environment are invited to apply. Experience in fields such as NPC, DNA origami, IDPs, MINFLUX, biophysics, single-molecule techniques, and optical imaging is
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physics, engineering, medicine, biology or a related field Practical experience in optics, signal processing and working with experimental setups (e.g. MATLAB) Interest in medical diagnostics and innovation
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for personally experienced past events, or episodic memory (EM), using a combination of behavioral, neuroimaging (fMRI) neurophysiology (EEG), and neuromodulation (TMS) methods. Traditional imaging studies focused
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(typically between 7-11pm) Mentorship and Laboratory Responsibilities (10%) Undergraduate mentorship (data entry, coding projects, image processing) Collaborate with a diverse team of researchers, including
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Number: JR89835 Position Summary The Integrated Biomedical Imaging Laboratory is seeking a Postdoctoral Research Associate interested in developing novel hybrid noninvasive imaging systems for studying
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the etiology of Cancer development, focusing on how deregulation of DNA motor proteins contributes to this process. Significant experience in protein purification and biochemistry is necessary for this position
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in sustainability, photonic and quantum technologies, new nanostructured materials, sensing, imaging and clean energy. The group adopts an interdisciplinary approach to provide leading-edge research in
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We are seeking a full-time Postdoctoral Research Assistant to join a cross disciplinary research project to improve our understanding of colorectal cancer. Deep learning has revolutionised image
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 1 day ago
line of research designed to establish a paradigm shift in our biomechanical understanding and clinical management of age-related mobility impairment toward feasible and cost-effective devices to modify
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potential applications in audio and music processing. Standard neural network training practices largely follow an open-loop paradigm, where the evolving state of the model typically does not influence