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tools Support ongoing research projects through model development, data analysis, technical reporting, and documentation Collaborate with NTU researchers, industrial partners, and other stakeholders
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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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Theme. The role involves leading and contributing to mixed-methods research across all stages of the research lifecycle, including design, delivery, analysis, publication and dissemination. You will work
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predictive modelling, pattern analysis and recognition. Demonstration of AI algorithms implementation To be considered for the role, you will be educated to a minimum of PhD level in an appropriate discipline
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scientific narratives Interest in microbiome science and women's health Preferred but not required: Experience with microbiome or multi-omic data analysis, causal inference methods, or infectious disease
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20th May 2026 Languages English English English The Department of Computer Science has a vacancy for a Postdoctoral Fellow in System-Level Analysis of Deep-Learning Acceleration Apply for this job
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• Applicants should have a PhD degree in civil or mechanical engineering or related disciplines • Possess fundamental knowledge in fatigue and fracture, structural integrity assessments and data driven
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experiments and analyses associated with experiments Create mitigation/alternative strategies when needed Literature and Data Analysis ~20% Read and analyze peer-reviewed literature surrounding water
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for the position: Master’s degree (120 ECTS credits) or equivalent qualifications in ecology or related areas when starting the PhD position. You have a solid methodological foundation in ecological data collection
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analysis - information provided in the CV and/or in the motivation letter; d.) Experience in paper or report writing, and presentations - information provided in the CV and/or in the motivation letter; e