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Data Science Health Innovation Fellow (6028U) Job #27188

In 2019, UC Berkeley, UCSF, Johnson & Johnson Innovation and Janssen Research & Development came together to establish the Data Science Health Innovation Fellowship Program, to bring together experienced data scientists with academic and industry researchers, to facilitate collaboration among scientists, engineers, clinicians, and entrepreneurs, to tackle complex problems in health and patient care and to accelerate innovation in healthcare through data-driven approaches.

This fellowship program offers a two-year research and entrepreneurial opportunity for seasoned data science professionals to apply computer science, data science, data engineering, and computational statistics research and development principles, along with relevant domain science knowledge, to complex problems and datasets, to advance understanding of health and improve patient care by providing meaningful clinical insights. The fellowship program will recruit serial cohorts of up to five outstanding data scientists per year from industry and academia. We are seeking applications from a wide range of backgrounds and with specializations across the burgeoning field of data science, such as artificial intelligence, cloud computing, developing and optimizing methodologies, software, and tools while working with various large datasets. The datasets Fellows have worked with may be healthcare related, such as electronic medical records, clinical notes, medical images, high-content microscopy and ‘omics, or should have comparable levels of scale and complexity. Fellows will receive training, support, and guidance from domain science and medical experts, including a mentor from each of the three collaborating organizations. The primary responsibility of the Fellows is to successfully identify and conduct interdisciplinary data-intensive research related to healthcare and use computational and data science technology as a tool to accomplish the aims of the research. 

BioQUEST Contact: Perot Saelao

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