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Field
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 1 month ago
public research institutions in the country. UNC-Chapel Hill offers postdocs comprehensive medical and vision coverage , paid leave, and benefits and services that support professional development and a
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an advantage Strong background in machine learning for image analysis and computer vision, ideally involving microscopy, time-lapse imaging, or other high-dimensional scientific imaging modalities
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for high-dimensional dependent data, and data sketching approaches for massive data. Opportunities to Contribute: Develop statistical/machine learning methodology for multi-modal imaging data integration
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Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig | Leipzig, Sachsen | Germany | 2 months ago
for a Postdoctoral Position in quantitative MRI Microscopy. Our vision is to develop and apply microstructure imaging and in-vivo histology using MRI (Weiskopf et al., Nature Rev. Phys. 2022 ). We
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IRCM - Cancer Research Institute of Montpellier | Montpellier, Languedoc Roussillon | France | 3 months ago
, Computer Vision, AI, Medical Imaging, or a related discipline. ● At least 3 years of research experience (post-PhD), ideally in an academic or public research setting. ● Solid grasp of deep learning theory
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and aspects related to safety and best practices. The candidate will make extensive use of state-of-the-art imaging, spectroscopy (Raman, electron microscopy, infrared, etc.) and scattering methods
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, optimization, and characterization integrating imaging, experimental metadata, and diffraction outcomes. Design and deploy computer vision methods to detect and track crystal growth. Develop closed-loop
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orthogonally to tonotopy. In collaboration with the Institut de la Vision, we will use new “Brainbow”-type fluorescent labeling tools to trace the neuronal connections between the various relays in the auditory
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expertise in machine learning, computational imaging, computer vision, or signal processing. Proficiency in scientific programming and modern ML frameworks, with the ability to implement and debug research
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vision and/or biomedical image analysis is essential, as well as the ability to manage own academic research and associated activities. Informal enquiries may be addressed to Jens Rittscher (jens.rittscher