Developing next-generation computational frameworks and automatic data analyses systems to analyze single-cell and spatial omics data, enabling new discoveries in developmental biology and disease modeling at Stanford University School of Medicine
Requirements
- Strong background in data science, or computational biology, especially in handling single-cell, spatial transcriptomics, or imaging data
- Proficiency in Python, R, or other scientific programming languages, with experience in software development and data pipeline automation
- Experience with cloud computing platforms (e.g., AWS, GCP) and collaborative development tools (e.g., GitHub, Docker)
- Knowledge of research translation and commercialization strategy, including startup planning and engagement with venture capital firms
- Strong knowledge of at least one programming language
- Working knowledge of latest software and design standards
Responsibilities
- Design and develop applications that may involve sophisticated data manipulation
- Maintain and update existing programs
- Troubleshoot and solve technical problems
- Create programs to meet reporting and analysis needs
- Design and implement user and operations training programs
- Document changes in software for end users
- Follow team software development methodology
Other
- Ability to work independently and collaboratively across interdisciplinary teams in a fast-paced academic or startup-like environment
- Excellent communication and organizational skills, with attention to detail and strong documentation practices
- Ability to assess user needs, troubleshoot complex technical issues, and design user-friendly, scalable applications
- Ability to recognize and recommend needed changes in user and/or operations procedures
- Basic knowledge of software engineering principles
