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Postdoctoral Associate AI and MRI Required Qualifications: (as evidenced by an attached resume) Doctoral Degree (or foreign equivalent) in Electrical and Computer Engineering, Computational Science
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Artificial Intelligence (AI), particularly in the development and application of Large Language Models (LLMs), to join our team working on predictive maintenance solutions. The ideal candidate will have
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processes. A demonstrated interest in data visualization and large-scale data analysis is highly desirable. The ideal candidate will have a keen interest in understanding complex biological systems
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with photogrammetry, LiDAR alignment, or large-scale 3D data, and deep learning-based 3D vision and graphics • Familiarity with image annotation tools and dataset iteration workflows • Contributions
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-series data assist in the supervision of PhD and Honours students working on related topics, including the analysis of large-scale sleep recordings from a dynamical systems perspective. About you The
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involve conducting large-scale data synthesis projects to better understand the drivers of urban metacommunities and biodiversity patterns. In particular, the lab is interested in understanding the drivers
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amenable to therapeutic targeting. This position will involve the application of advanced data science approaches to explore large-scale clinical datasets extracted from electronic health records, with
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place technologies and to develop digital twin algorithms to assist clinicians in developing treatment plans. Analyzes complex sensor data, works with a multidisciplinary team to develop health digital
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-PDF), data analysis and modelling for partially crystalline material systems Developing lab-based X-ray multimodalities: X-ray diffraction & imaging presentation of scientific results through
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RNA-seq data for testing and validation. Perform data analysis on large-scale RNA-seq data in pediatric cancer. This may involve the analysis of both scRNA-seq, bulk RNA-seq as well as new single-cell