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eRegistry data. The successful candidate will collaborate with researchers, PhD candidates, postdoctoral fellows, public health institutions and Ministries of Health in Ethiopia, Rwanda, Tanzania and Uganda
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application of machine learning and AI methods to large-scale, longitudinal, routinely collected eRegistry data. The successful candidate will collaborate with researchers, PhD candidates, postdoctoral fellows
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, metabolomics, proteomics) is an asset. Knowledge of data harmonization platforms (e.g., Maelstrom Research guidelines) is an asset. Experience with high-performance computing environments (Unix/HPC clusters) is
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