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Post-Doctoral Research Associate- College of Nursing - 24000000L7 Description Postdoctoral Researcher - Machine Learning and Big Data in Electronic Health Records and Other High Consequence
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must have the ability and is expected to self-assess their research skill set and identify weakness and secure learning resources to address these issues. In addition, the researcher needs to be willing
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responsibility of carrying out independent research related to application of machine learning and data mining techniques to analyze multiple data modalities related to corneal disease, including imaging, genetic
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disease Candidate will be responsible for performing all the experiments proposed for this project, including mouse learning memory behaviors, Western blot analysis and qRT-PCR, quantitative histology and
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background in biochemistry and in molecular and cell biology and will be responsible for performing all the experiments proposed for this project, including mouse learning memory behaviors, Western blot
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are encouraged to apply. All qualified applicants will receive equal consideration. The Suissa Lab values intellectual curiosity, continuous learning, and commitment to diversity, equity, inclusivity, and
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-health/e-health, data management, big data analysis, multilevel statistical analyses, machine learning, and a track record of publishing in peer-reviewed journals Qualifications Qualifications
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combining advances in robot design, model-based tissue mechanics, computer vision, and machine learning. Interested applicants are invited to submit their CV, cover letter, and contact information for three
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, parallel and distributed computing, machine learning, or data analytics. The successful candidate will possess excellent organizational, interpersonal, problem-solving and communication skills, including
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knowledge of cancer biology and bioinformatics is essential. Published evidence of experience in cancer biology and the tumor microenvironment is essential. The ability to learn quickly, work independently