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. Experience with Python programming. Familiarity with machine learning methods. Strong communication skills and ability to work collaboratively across theory and experiment. Desired Qualifications PhD in
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, numpy, scanpy, Squidpy, matplotlib, and others for single-cell and spatial analysis Interest in kidney research Exposure to machine learning and deep learning concepts Demonstrated ability to participate
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, and machine learning methods. Using regression analysis and vector autoregression (VAR) models, the study examines the relationship between macroeconomic variables and the performance of various
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cleaning and quality control, supervised and unsupervised machine learning, parametric and nonparametric statistical methods, deploying production models, and assisting with the communication of scientific
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understanding of all models of monitors and ECG machines utilized, be able to perform configuration on any specific monitor, replace defective equipment, report any equipment malfunctions to initiate repair, and
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, scalability, and effective performance across university use cases. Develops, trains, and fine-tunes machine learning models for a variety of university applications. Conducts experiments to evaluate model
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insurance, generous paid leave and retirement programs. To learn more about USC benefits, access the "Working at USC" section on the Applicant Portal at https://uscjobs.sc.edu. Research Grant or Time-limited
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materials using statistical mechanics, molecular simulations, and machine learning. Expectations Candidates will be responsible for: Developing multi-scale modeling methods for polymeric materials, using
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(e.g. Interspeech, ICASSP, SSW) and contribute to open-source release of corpus and models. Qualifications Requirements A doctoral degree in speech technology, machine learning, computational linguistics
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About the Opportunity JOB SUMMARY The Sr Machine Learning (ML) Engineer applies expertise in deploying and scaling AI pipelines across at least one major cloud platform (AWS, GCP, or Azure