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Yale Analog and RF Circuits and Systems (ARCS) Research Group, Department of Electrical and Computer Engineering, Yale University The Analog and RF Circuits and Systems Research Group in
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, design and analysis of virus-derived RNA libraries, and development of machine learning models for detecting functional elements in viral metagenomic datasets. This project is a collaboration with the
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Correction Circuits Design of parametric processes and quantum control of driven non-linear quantum devices Quantum computer architecture, hardware- and noise-aware compilers Computation with Dynamic Circuits
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in statistics, machine learning, clinical investigation, and research leadership; and develop an individual development plan addressing publications, funding, communication, networking, and the next
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. Position Overview The successful candidate will develop and apply advanced computational and machine learning methods to large-scale genomic, clinical, and imaging datasets, working across one or more of the
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Dr Rebecca Dikow - Director of Research Innovation, Yale University Libraries Dr Gary Motz - Head of Computer Systems, Yale Peabody Museum Jeff Campbell – Associate Director for Cultural Heritage
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experimental approaches such as non-coding CRISPR screens, the Massively Parallel Reporter Assay (MPRA), saturation mutagenesis, and synthetic sequence design, alongside machine-learning models of regulatory
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causal inference, machine learning, and artificial intelligence is desirable ● Experience with clinical, EHR, or biobank data analyses is desirable Application Instructions To apply: Interested