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Université Grenoble Alpes, laboratoire TIMC, équipe GMCAO | Grenoble, Rhone Alpes | France | about 8 hours ago
Post-doctoral Position In Medical Image Processing The Computer-Assisted Medical Interventions (CAMI) team at the TIMC laboratory (Grenoble, France) is seeking a highly motivated postdoctoral researcher
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clinical challenges within hospital settings. A deep understanding and hands-on experience in user-centred design, electronic circuitry, programming, and system controls within medical contexts are highly
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Description Post-Doctoral Fellow Position in Medical Image Processing (Deep Learning for Trauma CT) The Trauma Radiology AI Lab (TRAIL) in the Department of Radiology & Nuclear Medicine at the University
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Project title Multi-Modal Large Language Model for Medical Image Analysis Research period 2 years Abstract The proposed research project aims to develop a novel multi-modal large language model (MLLM
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Post-Doctoral Position - Medical Image Processing - (240000Y9) Post-Doctoral Fellow Position in Medical Image Processing (Deep Learning for Trauma CT) The Trauma Radiology AI Lab (TRAIL) in
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/Pytorch/scikitlearn deep learning platforms - Knowledge of biology and medical imaging methods: MRI, MRS - English: high level Website for additional job details https://emploi.cnrs.fr/Offres/CDD/UMR7348
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contract, with a base salary of $105,314 - $122,830 p.a., plus leave loading and a 17% superannuation About the opportunity The Image X Institute is a centre for innovation in radiation therapy and medical
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Chinese Institutes for Medical Research, Hansen Lab Position ID: Chinese Institutes for Medical Research -Hansen Lab -PRDD [#30416] Position Title: Position Type: Postdoctoral Position Location
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, transcriptomics, circuit mapping, 2P imaging, and nanoscopic imaging to understand how disruptions in neural-microglia signaling contributes to the disease. They have a dynamic group that offers an engaging work
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Colorectal Cancer - Stratification of Therapies through Adaptive Responses (CRC-STARS) programme, developing and applying cutting-edge mathematical methods to spatial transcriptomics imaging data in order to