University of California
Clinical Informatics / Bioinformatics Post-Doctoral Position
University of California, San Francisco, California, United States, 94199
Home > Clinical Informatics / Bioinformatics Post-Doctoral Position
Clinical Informatics / Bioinformatics Post-Doctoral Position
Location: 1700 4th Street, San Francisco, CA 94158, United States Job Posted Date: August 8, 2024 This is a full-time position for one year, with the possibility of extension. The scholar will engage in research projects related to developing or applying a range of machine learning (ML) models, including large language models (LLMs), and leverage real-world big electronic health records (EHR) data harmonized across the University of California (UC) health systems. At UC San Francisco (UCSF), real-world clinical data is linked across structured data and unstructured clinical texts and images, as well as genomics data for researchers and scientists to answer important research questions and develop impactful solutions. Projects the scholar will be involved in include: Developing AI-driven approaches to improve cancer, women’s health, and health disparity. Optimizing personalized treatments for cardiometabolic diseases. Developing multi-modal and multi-omics approaches for systems pharmacology. Investigating how AI/ML models can be used to promote health equity. Job Requirements: Qualifications needed: Majored in bioinformatics, computer sciences, or other fields relevant to quantitative sciences. Proficiency in Python, SQL, or other programming languages. Basic knowledge in machine learning and/or statistical learning. Knowledge or training in medicine, pharmacy, health sciences, systems biology, or pharmacology would be a great plus! Affiliated with the Department of Bioengineering and Therapeutic Sciences and Bakar Computational Health Sciences Institute.
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Location: 1700 4th Street, San Francisco, CA 94158, United States Job Posted Date: August 8, 2024 This is a full-time position for one year, with the possibility of extension. The scholar will engage in research projects related to developing or applying a range of machine learning (ML) models, including large language models (LLMs), and leverage real-world big electronic health records (EHR) data harmonized across the University of California (UC) health systems. At UC San Francisco (UCSF), real-world clinical data is linked across structured data and unstructured clinical texts and images, as well as genomics data for researchers and scientists to answer important research questions and develop impactful solutions. Projects the scholar will be involved in include: Developing AI-driven approaches to improve cancer, women’s health, and health disparity. Optimizing personalized treatments for cardiometabolic diseases. Developing multi-modal and multi-omics approaches for systems pharmacology. Investigating how AI/ML models can be used to promote health equity. Job Requirements: Qualifications needed: Majored in bioinformatics, computer sciences, or other fields relevant to quantitative sciences. Proficiency in Python, SQL, or other programming languages. Basic knowledge in machine learning and/or statistical learning. Knowledge or training in medicine, pharmacy, health sciences, systems biology, or pharmacology would be a great plus! Affiliated with the Department of Bioengineering and Therapeutic Sciences and Bakar Computational Health Sciences Institute.
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