Stanford University is looking to expand and enhance its data environment to support innovative healthcare solutions by developing large-scale data mining and predictive analytics capabilities, integrating diverse biomedical data sources into a comprehensive clinical data warehouse.
Requirements
- Proficiency in programming languages such as SQL, Python, and R is essential
- familiarity with cloud computing platforms like Google Cloud or Azure
- Experience with containerization technologies such as Docker
- orchestration platforms like Kubernetes is highly desirable
- handling HIPAA-protected PHI
- managing clinical EHR databases
- Knowledge of AI technologies including large language models (LLMs), natural language processing (NLP), and machine learning (ML) is preferred
Responsibilities
- designing, developing, and deploying complex biomedical informatics solutions
- conceptualizing system architectures
- implementing data integration workflows
- ensuring data quality and interoperability across various sources such as imaging systems, genomics platforms, and electronic health records
- develop technical specifications
- translate them into scalable software solutions
- document system configurations
Other
- Bachelor's degree in Software Engineering, Biotechnology, or a related field, along with at least five years of relevant experience or a combination of education and professional background.
- prior experience working within a medical school environment
- Familiarity with FHIR interoperability standards and tools like Epic Clarity is also advantageous.
- collaborating with diverse stakeholders to gather requirements
- mentoring junior developers
