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responsibilities Design, implement and benchmark deep machine learning models for large-scale cancer datasets that include genomics, transcriptomics, epigenomics and imaging data Collaborate closely with
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, normalization, dimensionality reduction) to downstream interpretation (differential expression, gene set enrichment, and cell type annotation). Implement Machine Learning Approaches, including deep learning
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transmon qubit at millikelvin temperatures . In addition, we have demonstrated millikelvin components for generating coherent microwave drive pulses and reset of qubits . Thus as a deep professional in cQED
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the Department of Computer Science, and the person is expected to engage in deep collaboration with research groups at Faculty of Science and Faculty of Pharmacy to enhance cutting edge research in the area. The
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expected to engage in deep collaboration with research groups at Faculty of Science and Faculty of Pharmacy to enhance cutting edge research in the area. The focus of the position is on application and