Position: Postdoctoral Fellow– Clinical cancer informatics and data science
A postdoctoral research opportunity is available at the University of California, San Francisco in the Hong laboratory (honglab.ucsf.edu). The Hong lab is part of both the Department of Radiation Oncology and the Bakar Computational Health Sciences Institute.
The Hong lab focuses on combining clinical domain knowledge with data science to generate insights from real world data, develop actionable computational tools, and evaluate the benefit of these advances for personalized cancer care. We have a specific interest and expertise in machine learning, natural language processing, computational data extraction, and imaging analytics. We apply these methods to identify new knowledge regarding clinical practice and patient outcomes, make actionable predictions, and identify new interventions. Our lab works from end-to-end along the development and implementation pipeline to develop tools for clinicians to make a meaningful difference in patient care.
The fellow will work on studies that utilize routine clinical data (including electronic health records and imaging) to develop algorithms to guide potential interventions in personalized oncology care. The fellow will take a lead role in key aspects of projects tailored to their prior experience, interests, and overlap with the lab’s core goals. They will join a multidisciplinary team of clinicians and scientists in the Department of Radiation Oncology and the Bakar Computational Health Sciences Institute.
The fellow will also be encouraged to take advantage of other training and learning opportunities within the UCSF Helen Diller Family Comprehensive Cancer Center, the Bakar Computational Health Sciences Institute, and other related entities at UCSF. We hope this experience will prepare the applicant for future opportunities in medicine and informatics.
Analyze healthcare-related data (may include electronic health records, imaging data, -omics, external data)
Develop analysis methods, software pipelines, machine learning algorithms
Work closely with other members of the lab and clinical/scientific collaborators
Communicate and publish results of studies
Ph.D. in bioinformatics, computer science, data science, statistics, or other quantitative/related field
Background working with health data
Demonstrated familiarity with biostatistics and machine learning/deep learning
Strong problem-solving skills, creative thinking, and ability to build new software tools
Excellent communication skills in written and verbal English
Documented experience analyzing complex datasets in programming languages such as R and/or Python
Successful publication record