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Field
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The School of Materials Science and Engineering (MSE) provides a vibrant and nurturing environment for staff and students to carry out inter-disciplinary research in key areas such as
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machine learning, computer vision, and medical image analysis, with publications in top-tier AI and medical image analysis conferences and journals, including CVPR, ICCV, ECCV, NeurIPS, MICCAI, TPAMI, TIP
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Group at the Department of Physics and Technology. We welcome applicants with a solid background in biophotonics, computational imaging or automation, who want to contribute to the development of cutting
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Food Science, Food Engineering, Materials Science, or a related field. A Master's or Ph.D. in a related research field is advantageous. Experience with instrumental texture, image analysis and particle
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required that the candidate’s undergraduate degree is also in Electrical Engineering or a related field deemed appropriate to the work plan. • Be enrolled in a doctoral programme, in accordance with
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engineering and computational biology methods to study development and regeneration, at a systems level, in tunicates. Tunicates, especially the genus Ciona, offer unique opportunities to leverage cutting edge
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of Biomedical Engineering (SBME). The successful candidate will work on advanced machine learning applications in computational pathology, medical imaging, and clinical text analysis. They will be expected
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We invite applications for a Research Fellow to join an interdisciplinary research team led by Dr. Sing Yian Chew (NTU). The successful candidate will contribute to an ongoing research program
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-oncology imaging and engineering, nucleic acids nanotechnology, computational biomedical imaging. We are seeking a person with preferred experience in cancer immunology, immune engineering, biomedical
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, this technology requires to experiment a change of paradigm to guarantee a sustainable development for the years to come. One pathway to achieve this paradigm shift relies on the development of data-driven