Senior In Vivo Translational Imaging Scientist

Genentech; South San Francisco (CA); On-site; USD 103,000 - 192,000; Full time

Benefits offered by this job

Relocation benefits

Discretionary bonus potential

Job summary

Genentech in South San Francisco seeks a scientist to drive preclinical and translational imaging research, bridging in vivo experiments, MRI/PET operations, and AI-enabled workflows to turn imaging data into therapeutic insights.

You will design and execute imaging studies, develop analysis pipelines in Python for HPC, and collaborate across biology, pharmacology, and computational biology to inform decisions.

Qualifications

• Ph.D. or equivalent in a quantitative imaging field.
• Hands-on in vivo imaging experience in regulated research environments.
• Strong MRI physics knowledge and artifact mitigation.
• Proficiency with Python for image analysis in Linux/Git workflows.

Responsibilities

• Design, execute, and optimize in vivo preclinical imaging studies.
• Operate and refine preclinical MRI protocols and quantitative analyses.
• Integrate data across PET/SPECT and biodistribution workflows.
• Develop reproducible image-processing pipelines and longitudinal analysis.
• Build Python-based analysis code for HPC workflows with containers.
• Apply AI tools and prompting to accelerate discovery and documentation.
• Collaborate with biologists and clinicians to translate endpoints into decisions.

Skills

Python

MRI physics

AI-assisted workflows

LLM prompting

3D/4D image analysis

Git & Linux

Education

Ph.D. or equivalent in quantitative imaging

Tools

Git

Linux

Docker

Apptainer/Singularity

Slurm

Job description

Genentech in South San Francisco seeks a scientist to drive preclinical and translational imaging research, bridging in vivo experiments, MRI/PET operations, and AI-enabled workflows to turn imaging data into therapeutic insights.

You will design and execute imaging studies, develop analysis pipelines in Python for HPC, and collaborate across biology, pharmacology, and computational biology to inform decisions.