49 algorithm-development "https:" "IMT Atlantique" Postdoctoral research jobs at THE UNIVERSITY OF HONG KONG
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for diagnosis and prognosis of different sarcomas. He/she will develop and train deep learning models with state-of-the-art algorithms based on histology whole slide images. They may also contribute to research
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multidisciplinary team specializing in medical imaging and algorithm development. Our work focuses on advancing the use of computer vision, deep learning, and machine learning for analyzing medical imaging modalities
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self-driven, highly motivated, creative with excellent communication skills in written and spoken English and Cantonese. Expertise and knowledge in AI deep learning model development on histology whole
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, School of Clinical Medicine, is seeking a highly motivated and talented researcher to join our multidisciplinary team specializing in medical imaging and algorithm development. Our work focuses on
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highly complex workflows. We aim to develop optimization models and algorithms to improve wafer processing sequences across semiconductor manufacturing tools, with the objectives of reducing cycle times
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research design and execution, including the development of analytical frameworks grounded in health economics across five priority areas: (i) HA Drug Formulary; (ii) assessment and adoption of medical
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organoid development, under the supervision of Professor Jade L. L. Teng. For inquiries, please contact Professor Teng at llteng@hku.hk . Further information about the Faculty can be found at https
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cell approaches with experimental epigenetics and stem cell platforms. Potential projects include: Developing AI/multimodal models (e.g., integrating single-cell omics, spatial transcriptomics
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of creating and sustaining a thriving clinical research ecosystem and driving development in Hong Kong and Greater Bay Area (GBA). In November 2024, the University of Hong Kong LKS Faculty of Medicine (HKUMed
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, transcriptomics data, Nanopore long read sequencing analysis and/or multimodality deep learning model development in different sarcomas. Publications in related fields will be a strong advantage. Opportunities for