Lead Computational Biologist - AI, Proteomics & PPI

UCSF Health, AG; San Francisco (CA); On-site; USD 180,000 - 240,000; Full time

Job summary

UCSF, through the Quantitative Biosciences Institute (QBI) in San Francisco, seeks a senior computational leader to advance AI/machine learning, structural biology, and systems biology across multiple research programs.

You will shape computational strategy, build reusable methods, and provide mentorship to scientists and staff while collaborating with international partners to translate large biomedical data into actionable insights.

Qualifications

• Bachelor's degree in biological science, computational / programming, or related area.
• Expert knowledge of structural bioinformatics and protein-protein interaction analysis.
• Minimum of ten years of experience designing computational methods for biological research.
• Expert knowledge of AI/ML methods applied to biology, including deep-learning protein structure prediction.
• Expert knowledge of modern biology including structural biology, proteomics, and genomics.
• Ability to interpret experimental readouts and translate predictions into hypotheses.
• Ability to lead across multi-year, multi-investigator programs with multiple UCSF units.
• Strong interpersonal skills and ability to communicate technical information clearly.
• Ability to interface with management on a regular basis.
• Experience providing authoritative technical consultation to senior investigators.
• Knowledge of cloud platforms, containerization, and version control.
• Knowledge of research data governance and data management practices.

Responsibilities

• Functions as a recognized expert in computational bioinformatics, AI/machine learning, and structural biology.
• Develops and directs advanced computational approaches used across multiple major QBI research programs and collaborations.
• Applies expert knowledge to complex problems in protein-protein interaction prediction, structural modeling, and large-scale data integration.
• Provides computational leadership across multi-investigator programs involving UCSF units and external collaborators.
• Shapes computational strategy, establishes standards and reproducibility practices, and develops reusable resources.
• Represents QBI and UCSF computation through publications, presentations, and shared resources.
• Provides technical direction and mentorship to computational staff, postdocs, and students.

Skills

Python

AI in biology

Protein structure

LLM usage

Leadership

Cloud platforms

Containerization

Version control

Graph neural networks

Education

Bachelor's degree in biological science

PhD in biophysics / computational biology

Tools

Containerization

Job description

UCSF, through the Quantitative Biosciences Institute (QBI) in San Francisco, seeks a senior computational leader to advance AI/machine learning, structural biology, and systems biology across multiple research programs.

You will shape computational strategy, build reusable methods, and provide mentorship to scientists and staff while collaborating with international partners to translate large biomedical data into actionable insights.