Scientist 3, In Vivo Translational Imaging

The Opportunity

In the Department of Translational Imaging, you will drive preclinical and translational imaging research to help deliver life-changing healthcare solutions. You will work within a highly collaborative, multidisciplinary environment, moving seamlessly between in vivo experimentation, scanner operations (preclinical MRI/PET), quantitative analysis, and modern AI-enabled computational workflows to translate imaging data into therapeutic discoveries.

Key Responsibilities

• Design, execute, and optimize in vivo preclinical imaging studies following approved ethical, compliance, and institutional safety standards.
• Operate and refine preclinical MRI protocols, applying quantitative methods to characterize anatomy, microstructure, physiology, and therapeutic treatment responses.
• Support multimodal imaging studies by integrating data across nuclear imaging (PET/SPECT) and biodistribution workflows.
• Develop and maintain robust, reproducible image-processing pipelines for registration, segmentation, quantitative feature extraction, and longitudinal analysis.
• Build scalable, reproducible analysis code primarily in Python, executing workflows across High-Performance Computing (HPC) clusters utilizing containers and GPU acceleration.
• Apply AI tools, prompting techniques, and coding agents to accelerate scientific discovery, streamline analysis prototyping, and enhance code documentation.
• Partner cross-functionally with biologists, pharmacologists, computational biologists, and research leaders to translate multimodal imaging endpoints into actionable scientific decisions.

Who You Are

• You hold an advanced degree (Ph.D. or equivalent combined education and experience) in Biomedical Engineering, Biophysics, Physics, Imaging Science, Computer Science, or a related quantitative discipline.
• You bring practical hands-on experience or demonstrated comfort conducting in vivo model procedures within institutionally regulated research environments.
• You possess strong working knowledge of MRI physics and image formation, including pulse sequences, contrast mechanisms, signal-to-noise optimization, and artifact mitigation.
• You have demonstrated expertise analyzing 3D/4D quantitative imaging data using Python (or equivalent scientific programming) within Linux and version-controlled (Git) environments.
• You have practical fluency leveraging AI-assisted computational tools, LLM prompting, or coding agents to accelerate research and development workflows.

Preferred

• Hands-on experience with preclinical PET or SPECT acquisition, reconstruction, biodistribution analysis, and quantitative multimodal data integration.
• Experience developing or optimizing custom MRI pulse sequences, novel reconstruction algorithms, quantitative imaging biomarkers, and/or contrast-agent dynamics.
• Solid understanding of computer vision, image processing, and machine learning/deep learning methods for biomedical image segmentation, registration, and automated quality control.
• Proven experience working on High-Performance Computing (HPC) clusters with workload managers (such as Slurm), containerization technologies (Docker, Apptainer/Singularity), and GPU acceleration.
• Proficiency in additional scientific programming languages and platforms (e.g., MATLAB, R, C/C++, ITK, 3D Slicer, or equivalent biomedical toolkits).
• Background in drug discovery, translational medicine, or oncology/neuroscience biomarker development, with a track record of bridging imaging metrics to pharmacological mechanism of action.
• Demonstrable scientific curiosity, agility, and comfort navigating seamlessly between hands-on scanner/bench work and dry-lab computational modeling.