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statistical and machine learning methods applied to large claims and electronic health record databases and multimodal data, including physiological waveforms and medical imaging. We foster a collaborative and
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microscopy. • Expertise in metabolomics with mass spectrometry is desired. • Strong general computer skills, experience with databases and scientific applications, and ability to quickly learn and master
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, observations, a hierarchy of numerical models, and machine-learning methods to understand their formation, dynamics, and predictability. The successful candidate will have substantial freedom to develop
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or machine learning is highly desirable Prior experience with liquid biopsy work is welcome but not required Proven ability to think creatively, work collaboratively, and communicate effectively Fluency in
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well as introductory nutrition courses. The successful candidate will teach introductory biology courses and upper-level courses in their area of specialty. The successful candidate will also provide a proposal
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, Yale New Haven Hospital, the Office of Academic and Professional Development, Central Human Resources, the Office of Postdoctoral Affairs and the Office of International Students and Scholars
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development, and machine learning. The ideal candidate would conduct highly collaborative dry lab research in areas of focus aligned with departmental strengths in learning and memory, decision making, motor
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for highly motivated postdoctoral candidates with a PhD in bioengineering deep knowledge in computational biology and machine learning. Candidates with a molecular biology or engineering degrees with
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quantitative measurement to these system -from single molecules and nanoparticles to living systems, enabled by advances in instrumentation, spectroscopy, mass spectrometry, microscopy, and machine learning
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machine learning. The ideal candidate would conduct highly collaborative dry lab research in areas of focus aligned with strengths in CAPS, the Department of Neuroscience, and the growing computational