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Field
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research programme is to use genetic, molecular and cellular, and imaging/image analysis approaches to understand the development and function of the vertebrate inner ear, the organ of hearing and balance
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participates in ensuring the smooth functioning and operation of the program, and participates in UBHC-wide meetings, performance improvement activities, committees and task forces as assigned. In clinical
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such as ecology, economy and social sciences. ZMT aims to use data science tools, including computer vision and deep learning, for the study of rapid changes in tropical coastal socioecological systems
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or instructional technology field, including media production, teaching with technology, or web distribution. Works with a wide variety of media technologies, networks, and computer hardware and software, applying
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multidisciplinary teams to uncover patterns, trends, and relationships in aging data. Required Qualifications: (as evidenced by an attached resume) * Ph.D. degree in Data Science, Computer Science, Bioinformatics
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The Department of Computer Science seeks to employ 2 postdoctoral researchers to work on a new project in the area of LLMs/multi-agent systems, under the direction of PI Professor Michael Wooldridge
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Skip to main content home Faculty of Science chevron-right Engage with us chevron-right Amgen Scholars Program Faculty of Science Engage with us Amgen Scholars Program Amgen Scholars Program
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physiological processes at the molecular, cellular, tissue and systems level of organisation. In so doing we provide a bridge to translational medicine, and interface between physical and life sciences. We
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administrative team, administers and designs operational processes and resolves complex fellow and faculty issues. Acts as the senior resource specialist for the fellow candidates, clinical/postdoctoral fellows
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, Computer Science, Bioinformatics, Biomedical Engineering, Computational Biology, Neuroscience, or a closely related field. ● 5 years of experience (strong expertise) in data analysis and machine learning