The Deisseroth Lab at Stanford University is looking for a Computational Biology Research Scientist to develop software for a recently developed revolutionary technology for spatial gene expression mapping (STARmap: Spatial Transcript Amplicon Readout mapping). This person will be responsible for the acquisition, processing, and analysis of high-dimensional, single-cell transcriptomic data applied to neuroscience experiments aimed at understanding the function of neural circuits that produce behavior in health and disease. This job will entail working closely with experimentalists to design and interpret spatial transcriptomic experiments, as well as building vital software infrastructure for data processing and storage. The ideal candidate would have a Masters or above in a quantitative field (computer science, applied mathematics, bioinformatics) as well as knowledge of modern molecular biology and genomics. Strong software engineering in Python and data analysis experience (statistics, machine learning, numerical computing) is required. Experience with cloud computing infrastructure (AWS or Google Cloud) is a plus. This person should be self-driven and capable of implementing large parts of a project independently, while also exhibiting excellent communication skills required for working in a highly collaborative environment.
Duties include:
- Propose, conceptualize, design, implement, and develop solutions for difficult and complex applications independently.
- Oversee testing, debugging, change control, and documentation for major projects.
- Supervise professional staff, as necessary, working on all phases of application development projects.
- Engage in long-term strategic planning.
- Define complex application development administration and programming standards.
- Oversee the support, maintenance, operation, and upgrades of applications.
- Troubleshoot and resolve complex technical problems.
- Review the physical design of existing systems for optimizing performance.
- Lead projects, as necessary, for special systems and application development in areas of complex problems.
- Work with other technical professionals to develop standards and implement best practices.
DESIRED QUALIFICATIONS:
Master’s degree in Computational Biology, Bioinformatics, Applied Mathematics, Computer Science, Electrical Engineering, or other quantitative field preferred.
EDUCATION & EXPERIENCE (REQUIRED):
Bachelor's degree and eight years of relevant experience, or a combination of education and relevant experience.
KNOWLEDGE, SKILLS AND ABILITIES (REQUIRED):
- Ability to quickly learn and adapt to new technologies and programming tools.
- Demonstrated experience in designing, developing, testing, and deploying applications.
- Strong understanding of data design, architecture, relational databases, and data modeling.
- Thorough understanding of all aspects of software development life cycle and quality control practices.
- Ability to define and solve logical problems for highly technical applications.
- Strong communication skills with both technical and non-technical clients.
- Demonstrated experience leading activities on structured team development projects.
- Ability to select, adapt, and effectively use a variety of programming methods.
- Ability to recognize and recommend needed changes in user and/or operations procedures.
PHYSICAL REQUIREMENTS:
- Constantly perform desk-based computer tasks.
- Frequently sit, grasp lightly/fine manipulation.
- Occasionally stand/walk, writing by hand.
- Rarely use a telephone, lift/carry/push/pull objects that weigh up to 10 pounds.
WORKING CONDITIONS:
May work extended hours, evening and weekends.
WORK STANDARDS:
- Interpersonal Skills: Demonstrates the ability to work well with Stanford colleagues and clients and with external organizations.
- Promote Culture of Safety: Demonstrates commitment to personal responsibility and value for safety; communicates safety concerns; uses and promotes safe behaviors based on training and lessons learned.
- Subject to and expected to comply with all applicable University policies and procedures, including but not limited to the personnel policies and other policies found in the University's Administrative Guide.