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source and keeps it compressed throughout its lifecycle. Pioneered by AU, these advanced compression techniques allow for on-the-fly data compression, support analytics and machine learning (ML) without
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knowledge in building ventilation systems, heat transfer, fluid dynamics, machine learning, data analysis, and coding e.g., Python. Understand sensors, actuators, data acquisition, and control systems
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for translatome analysis Expertise in integrating large-scale multiomic datasets, including machine learning based approaches Excellent written communication skills demonstrated by an outstanding publication track
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data integration and analysis Integrate phylogenomic and functional data using machine-learning approaches for candidate gene prioritisation Contribute to software and web-tool development Present