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Field
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, machine learning, multiscale and multiphysics simulation, computational anatomy, medical image analysis, and integration of wearables and biosignal processing, applied to conditions ranging from cardiac
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integrates molecular, imaging, and neurophysiological approaches to understand neurodevelopmental disorders, with particular focus on perineuronal nets and their role in seizure susceptibility. This position
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You will: Lead a project on synaptic and circuit mechanisms underlying sensory processing in V1 Implement advanced in vivo approaches, including two-photon imaging, optogenetics, and/or
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and medical challenges. The Institute of Biological and Medical Imaging (IBMI) at Helmholtz Munich and the Chair of Biological Imaging (CBI) at the Technical University of Munich (TUM) are an integrated
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reconstruction and processing. Candidates are expected to have a strong background in medical imaging, experience in imaging system evaluation, deep learning and clinical investigation. Brief Description of Duties
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following skills: Strong interest in the field of neuroimaging, psychiatry and genetics. Computer skills: Strong level in the main informatics software (FSL, Freesurfer, fMRIprep) and coding languages (R
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National Aeronautics and Space Administration (NASA) | Pasadena, California | United States | about 2 hours ago
cycles. Understanding these complex interactions requires measurements that go beyond traditional multi-spectral imaging. Imaging spectroscopy—capturing the full contiguous spectrum from the Visible
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reconstruction and processing. Candidates are expected to have a strong background in medical imaging, experience in imaging system evaluation, deep learning and clinical investigation. Brief Description of Duties
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artificial intelligence with a preferred focus on computer vision and medical image analysis. Preferred Qualifications: PhD in Medical Physics, Bioengineering, Biomedical Engineering, Physics, Computer Science
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multimodal vision-language models for prompt-based 3D medical image segmentation Work with large-scale clinical CT datasets and scalable deep learning pipelines Validate models in close collaboration with