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resonance imaging) Fluency in English Experience and knowledge: Required: Experience in computer programming Expertise in Python programming for Machine and Deep Learning, e.g., sklearn, pytorch, tensorflow
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signal/image processing, computer science, applied mathematics, or a related field, obtained less than 3 years before the date of hire. Essential skills, knowledge and experience: Excellent command
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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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the Quantitative Imaging Platform of Villefranche (PIQv; https://sites.google.com/view/piqv ), which oversees the operation of the tools that the team develops. Those tools include imaging sensors, such as the
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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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kidney injury, providing deeper insight into the cellular processes that support renal immune function. Candidates must have a proven record of scientific achievement during graduate and/or postdoctoral
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resonance imaging) Fluency in English Experience and knowledge: Required: Experience in computer programming Expertise in Python programming for Machine and Deep Learning, e.g., sklearn, pytorch, tensorflow
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translational research team and help shape the future of pediatric leukemia treatment through image-based drug profiling. We’re looking for a dedicated Postdoc to join our research team, where science meets
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Inria, the French national research institute for the digital sciences | Rennes, Bretagne | France | 7 days ago
research lab consists of more than 20 researchers, faculty members, PhD students, engineers and interns, working in the field of image processing and neuroimaging. The team targets the detection and
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pediatric AML Development of advanced computer vision models for pipeline improvements: https://doi.org/10.1016/j.xcrm.2025.102304 Multi-omics analysis including high-throughput data from image-based drug