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. Experience in molecular modelling, simulations, AI, and machine learning applied to proteins. A track record of research outputs, including publications and presentations at national or international level
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of excellence in research, innovation, and learning for all faculty, staff and students. Our commitment to employment equity helps achieve inclusion and fairness, brings rich diversity to UBC as a workplace, and
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knowledge in one or more areas and be enthusiastic to new learning opportunities. Key Responsibilities: The position is responsible for design and implementation of prototypes, electronic control, data
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: signal processing, advanced data analysis, statistics, and machine learning – Experience in safe laboratory procedures. Effective verbal and written communication skills. Laboratory experience
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background in AI—such as knowledge of machine learning or neural networks—will be an advantage. The appointee is expected to conduct focused research, publish scholarly outputs in reputable, peer-reviewed
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machine learning to support early detection and prioritisation of patients at risk of vision loss. The role involves leading PPIE activities to ensure that patient perspectives and lived experiences shape
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, timely, and thorough. Works well both independently, with little supervision, and in a team setting. Knowledge of genetics and genetic concepts or desire to learn. Strong computer skills and experience
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machine learning. Compensation will be consistent with Penn State’s standard rates. Job Duties: Develop and maintain web scraping scripts to collect data from various online sources Clean, organize, and
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access to various professional development opportunities, including a membership to Academic Impressions, LinkedIn Learning, and UT Dallas Bright Leaders Program. Visit https://hr.utdallas.edu/employees