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Field
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experience Required Qualifications: PhD in Electrical Engineering or a closely related field. Preferred: Demonstrated expertise in AI/ML, including deep learning, computer vision, LLMs, VLMs, multimodal AI
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at the intersection of computer vision, micro-electronics analysis, and hardware security, and will work under the supervision of researchers within the Department of Intelligent Systems. The PhD researcher will be
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with scientific programming and quantitative data analysis, particularly in Python, is welcomed. Experience with droplet generation, thermal diagnostics, image processing, or automated experimental
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Resonance Imaging to Molecular Signatures: Generative AI for Virtual Biopsy in Gliomas - Gliogen X will be to develop a non-invasive virtual biopsy based on magnetic resonance imaging to molecularly classify
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 3 hours ago
world. Position Summary This Postdoctoral Research Associate will conduct advanced research in artificial intelligence, machine learning, computer vision, and medical image analysis. The position will contribute
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of Biomedical Engineering and Imaging Sciences (https://www.kcl.ac.uk/bmeis ) is a cutting-edge research and teaching School dedicated to development, translation and clinical application within medical imaging
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detection and applications in quantum communications and single-photon imaging. With single-photon avalanche diode (SPAD) detectors, we initiated and led collaborations to produce the first custom-designed
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foundational methods for integrating single-cell and clinical transcriptomes; and train, fine-tune, and validate deep learning models using multi-omics and imaging data to predict clinical outcomes such as
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· Ability to work as a team · Proficient communication skills, written and oral · Anticipates and solves problems · High degree of initiative Preferred skills: PhD in Virology with HIV research · Image
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, fabrication, sealing and assembly. Demonstrated capability in chemical process design for experimental or prototype systems, including material and energy balances, process flow diagrams, piping and