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. The ideal candidate will possess not only a deep conceptual understanding of neuroscience but also advanced technical expertise in machine learning, artificial intelligence, and data modeling approaches. We
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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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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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, 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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engineering and clinical physiology. Projects may involve signal quality assessment, artifact detection, waveform segmentation, feature extraction, hemodynamic modeling, time-series analysis, machine learning
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paired with computational biology and machine learning to develop predictive AI models of how cells interpret and respond to the surrounding extracellular matrix. Required Qualifications: We are looking
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precursors of breast neoplasia progress to invasive breast cancer. They will be part of an interdisciplinary team of pathologists, immunologists, and computer scientists. The project builds on our previous
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distribution. Both projects will develop the Fontan emulator to be patient-specific, MRI compatible, computer controlled, and quantitatively evaluated using advanced bench-top, CFD/FSI simulation, and MRI-based
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groups from Stanford and beyond working on complementary approaches to T cell recognition. Our group provides an intellectually rich environment, with scientists applying genetics, proteomics and machine