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maintaining Google Cloud Platform pipelines for smartphone, wearable, molecular and clinical datasets to advance early detection and monitoring of pulmonary arterial hypertension. You will work closely with
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experience Strong practical knowledge of machine learning with large datasets Experience : Experience with cloud-based, parallel, or distributed computing environments Hands-on experience developing or
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experience Strong practical knowledge of machine learning with large datasets Experience : Experience with cloud-based, parallel, or distributed computing environments Hands-on experience developing or
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experience Strong practical knowledge of machine learning with large datasets Experience : Experience with cloud-based, parallel, or distributed computing environments Hands-on experience developing
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experience Strong practical knowledge of machine learning with large datasets Experience : Experience with cloud-based, parallel, or distributed computing environments Hands-on experience developing
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data engineering platforms such as the Databricks Data Intelligence Platform to process large-scale batch and streaming workloads using Python and SQL; develop and supports solutions across cloud
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healthcare and research use cases; develop and operate across cloud-based platforms (e.g., Azure, AWS), Data Engineering Platforms (e.g. Databricks, Fabric), and high-performance computing (HPC) or
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researchers, research centres, IT Services colleagues, and external partners to support High Performance Computing (HPC), research data storage platforms, cloud-based services, and associated research
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-governed services that support institutional priorities across teaching, research, administration, and innovation. The successful candidate will bring strong technical expertise in AI platforms, cloud
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Creative Cloud, including Photoshop, Illustrator, After Effects, and Premiere Pro. Preferred Qualifications: Master’s degree in Digital Media, Creative Media, Graphic Design, Media Arts, or related